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STAT200: Assignment #2 - Descriptive Statistics Analysis Writeup - Template Page 3 of 3 University of Maryland University College STAT200 - Assignment #2: Descriptive Statistics Analysis and Writeup Identifying Information Student (Full Name): Class: Instructor: Date: Introduction: Use the same scenario you submitted for the first assignment with modifications using your instructor’s feedback, if needed. Include Table 1: Variables Selected for the Analysis you used in Assignment #1 to show the variables you selected for analysis. Table 1. Variables Selected for the Analysis Variable Name in data set Description Type of Variable (Qualitative or Quantitative) Variable 1: “Income” Annual household income in USD. Quantitative Variable 2: Variable 3: Variable 4: Variable 5: Data Set Description and Method Used for Analysis: Results: Variable 1: Income Numerical Summary. Table 2. Descriptive Analysis for Variable 1 Variable n Measure(s) of Central Tendency Measure(s) of Dispersion Variable: Income Median= SD = Graph and/or Table: Histogram of Income (Place Histogram here) Description of Findings. Variable 2: (Fill in name of variable) Numerical Summary. Table 3. Descriptive Analysis for Variable 2 Variable n Measure(s) of Central Tendency Measure(s) of Dispersion Variable: Graph and/or Table. (Place Graph or Table Here) Description of Findings. Variable 3: (Fill in name of variable) Numerical Summary. Table 4. Descriptive Analysis for Variable 3 Variable n Measure(s) of Central Tendency Measure(s) of Dispersion Variable: Graph and/or Table. (Place Graph or Table Here) Description of Findings. Variable 4: (Fill in name of variable) Numerical Summary. Table 5. Descriptive Analysis for Variable 4 Variable N Mean/Median St. Dev. Variable 4: Graph and/or Table. (Place Graph or Table Here) Description of Findings. Variable 5: (Fill in name of variable) Numerical Summary. Table 6. Descriptive Analysis for Variable 5 Variable n Measure(s) of Central Tendency Measure(s) of Dispersion Variable: Graph and/or Table. (Place Graph or Table Here) Description of Findings. Discussion and Conclusion. Briefly discuss each variable in the same sequence as presented in the results. What has the highest expenditure? What variable has the lowest expenditure? If you were to recommend a place to save money, which expenditure would it be and why? Note: The section should be no more than 2 paragraphs. STAT200 Introduction to Statistics Dataset for Written Assignments Description of Dataset: The data is a random sample from the US Department of Labor’s 2016 Consumer Expenditure Surveys (CE) and provides information about the composition of households and their annual expenditures (https://www.bls.gov/cex/). It contains information from 30 households, where a survey responder provided the requested information; it is all self-reported information. This dataset contains four socioeconomic variables (whose names.
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STAT200 Assignment #2 - Descriptive Statistics Analysis Write.docx
STAT200: Assignment #2 - Descriptive Statistics Analysis Writeup - Template
Page 1 of 3
University of Maryland University College
STAT200 - Assignment #2: Descriptive Statistics Analysis and Writeup
Identifying Information
Student (Full Name):
Class:
Instructor:
Date:
Introduction:
Use the same scenario you submitted for the first assignment with modifications using your instructor’s
feedback, if needed. Include Table 1: Variables Selected for the Analysis you used in Assignment #1 to
show the variables you selected for analysis.
Table 1. Variables Selected for the Analysis
Variable Name in data
set
Description Type of Variable (Qualitative or
Quantitative)
Variable 1: “Income”
Annual household income in
USD.
Quantitative
Variable 2:
Variable 3:
Variable 4:
Variable 5:
Data Set Description and Method Used for Analysis:
Results:
Variable 1: Income
Numerical Summary.
STAT200: Assignment #2 - Descriptive Statistics Analysis Writeup - Template
Page 2 of 3
Table 2. Descriptive Analysis for Variable 1
Variable n Measure(s) of Central Tendency Measure(s) of Dispersion
Variable: Income Median= SD =
Graph and/or Table: Histogram of Income
(Place Histogram here)
Description of Findings.
Variable 2: (Fill in name of variable)
Numerical Summary.
Table 3. Descriptive Analysis for Variable 2
Variable n Measure(s) of Central Tendency Measure(s) of Dispersion
Variable:
Graph and/or Table.
(Place Graph or Table Here)
Description of Findings.
Variable 3: (Fill in name of variable)
Numerical Summary.
Table 4. Descriptive Analysis for Variable 3
Variable n Measure(s) of Central Tendency Measure(s) of Dispersion
Variable:
Graph and/or Table.
(Place Graph or Table Here)
STAT200: Assignment #2 - Descriptive Statistics Analysis Writeup - Template
Page 3 of 3
Description of Findings.
Variable 4: (Fill in name of variable)
Numerical Summary.
Table 5. Descriptive Analysis for Variable 4
Variable N Mean/Median St. Dev.
Variable 4:
Graph and/or Table.
(Place Graph or Table Here)
Description of Findings.
Variable 5: (Fill in name of variable)
Numerical Summary.
Table 6. Descriptive Analysis for Variable 5
Variable n Measure(s) of Central Tendency Measure(s) of Dispersion
Variable:
Graph and/or Table.
(Place Graph or Table Here)
Description of Findings.
Discussion and Conclusion.
Briefly discuss each variable in the same sequence as presented in the results. What has the highest
expenditure? What variable has the lowest expenditure? If you were to recommend a place to save
money, which expenditure would it be and why? Note: The section should be no more than 2
paragraphs.
STAT200 Introduction to Statistics
Dataset for Written Assignments
Description of Dataset:
The data is a random sample from the US Department of Labor’s 2016 Consumer Expenditure Surveys.
STAT200 Assignment #2 - Descriptive Statistics Analysis Writeup -.docx
STAT200: Assignment #2 - Descriptive Statistics Analysis Writeup - Template
Page 3 of 3
University of Maryland University College
STAT200 - Assignment #2: Descriptive Statistics Analysis and Writeup
Identifying Information
Student (Full Name):
Class: STAT 200
Instructor:
Date:
Introduction:
Use the same scenario you submitted for the first assignment with modifications using your instructor’s feedback, if needed. Include Table 1: Variables Selected for the Analysis you used in Assignment #1 to show the variables you selected for analysis.
Table 1. Variables Selected for the Analysis
Variable Name in data set
Description
Type of Variable (Qualitative or Quantitative)
Variable 1: “Income”
Annual household income in USD.
Quantitative
Variable 2: “Marital Status”
Martial Status as the Head of Household
Qualitative
Variable 3: “Family Size”
Total number of people in the house to include adults and children
Quantitative
Variable 4: “Annual Expenditures”
Total amount of annual expenditures
Quantitative
Variable 5: “Age Head of Household”
Age of Head of Household
Quantitative
Data Set Description and Method Used for Analysis:
Results:
Variable 1: Income
Numerical Summary.
Table 2. Descriptive Analysis for Variable 1
Variable
n
Measure(s) of Central Tendency
Measure(s) of Dispersion
Variable: Income
Median=
SD =
Graph and/or Table: Histogram of Income
(Place Histogram here)
Description of Findings.
Variable 2: (Fill in name of variable)
Numerical Summary.
Table 3. Descriptive Analysis for Variable 2
Variable
n
Measure(s) of Central Tendency
Measure(s) of Dispersion
Variable:
Graph and/or Table.
(Place Graph or Table Here)
Description of Findings.
Variable 3: (Fill in name of variable)
Numerical Summary.
Table 4. Descriptive Analysis for Variable 3
Variable
n
Measure(s) of Central Tendency
Measure(s) of Dispersion
Variable:
Graph and/or Table.
(Place Graph or Table Here)
Description of Findings.
Variable 4: (Fill in name of variable)
Numerical Summary.
Table 5. Descriptive Analysis for Variable 4
Variable
N
Mean/Median
St. Dev.
Variable 4:
Graph and/or Table.
(Place Graph or Table Here)
Description of Findings.
Variable 5: (Fill in name of variable)
Numerical Summary.
Table 6. Descriptive Analysis for Variable 5
Variable
n
Measure(s) of Central Tendency
Measure(s) of Dispersion
Variable:
Graph and/or Table.
(Place Graph or Table Here)
Description of Findings.
Discussion and Conclusion.
Briefly discuss each variable in the same sequence as presented in the results. What has the highest expenditure? What variable has the lowest expenditure? If you were to recommend a place to save money, which expenditure would it be and why? Note: The section should be no more than 2 paragraphs.
STAT200 Introduction to Statistics
Dataset for Written Assignments
Description of Dataset:
The data is a random sample from the US Department of Labor’s 2016 Consumer Expenditure Surveys (CE) and provides informat.
STAT200 Introduction to StatisticsDataset for Written Assignment.docx
STAT200 Introduction to Statistics
Dataset for Written Assignments
Description of Dataset:
The data is a random sample from the US Department of Labor’s 2016 Consumer Expenditure Surveys (CE) and provides information about the composition of households and their annual expenditures (https://www.bls.gov/cex/). It contains information from 30 households, where a survey responder provided the requested information; it is all self-reported information. This dataset contains four socioeconomic variables (whose names start with SE) and four expenditure variables (whose names start with USD).
Description of Variables/Data Dictionary:
The following table is a data dictionary that describes the variables and their locations in this dataset (Note: Dataset is on second page of this document):
Variable Name
Location in Dataset
Variable Description
Coding
UniqueID#
First Column
Unique number used to identify each survey responder
Each responder has a unique number from 1-30
SE-MaritalStatus
Second Column
Marital Status of Head of Household
Not Married/Married
SE-Income
Third Column
Annual Household Income
Amount in US Dollars
SE-AgeHeadHousehold
Fourth Column
Age of the Head of Household
Age in Years
SE-FamilySize
Fifth Column
Total Number of People in Family (Both Adults and Children)
Number of People in Family
USD-Annual Expenditures
Sixth Column
Total Amount of Annual Expenditures
Amount in US Dollars
USD-Food
Seventh Column
Total Amount of Annual Expenditure on Food
Amount in US Dollars
USD-Entertainment
Eighth Column
Total Amount of Annual Expenditure on Entertainment
Amount in US Dollars
USD-Education
Ninth Column
Total Amount of Annual Expenditure on Education
Amount in US Dollars
How to read the data set: Each row contains information from one household. For instance, the first row of the dataset starting on the next page shows us that: the head of household is not married and is 40 years old, has an annual household income of $98,717, a family size of 3, annual expenditures of $56,393, and spends $7,036 on food, $106 on entertainment, and $213 on education.
UniqueID#
SE-MaritalStatus
SE-Income
SE-AgeHeadHousehold
SE-FamilySize
USD-AnnualExpenditures
USD-Food
USD-Entertainment
USD-Education
1
Not Married
98717
40
3
56393
7036
106
213
2
Not Married
96572
59
2
56515
7179
95
349
3
Not Married
96690
57
2
56097
6822
88
252
4
Not Married
96664
53
3
55558
7051
83
295
5
Not Married
96886
44
2
55321
6982
79
312
6
Not Married
96522
43
4
56152
6991
101
237
7
Not Married
97912
49
1
55704
6937
97
277
8
Not Married
96727
39
2
56440
7051
93
222
9
Not Married
96928
43
3
55932
6953
105
273
10
Not Married
95744
52
4
55963
7040
105
340
11
Not Married
97681
53
4
56124
7097
108
263
12
Not Married
95432
51
1
55120
7089
84
274
13
Not Married
94929
59
2
55247
6948
97
236
14
Not Married
96621
54
2
55746
7000
106
322
15
Not Married
95366
48
2
57082
7130
90
305
16
Married
101829
45
4
82385
10821
201
810
17
Married
98309
51
2
75776
9118
117
477
18
Married
112559
39
3
80.
5University of Maryland University CollegeSTAT200 - Assignm.docx
5
University of Maryland University College
STAT200 - Assignment #1: Descriptive Statistics Data Analysis Plan
Identifying Information
Amber Wilson
Stat 200 6755
Dr.Barnes
11/4/19
Scenario:
I am a student conducting a research to determine the main factors contributing expenditures of a given family. Data given provide information on income, expenditure on food, family size, annual expenditure and expenditure on entertainment.
The selected variables are shown in the table below.
Table 1. Variables Selected for the Analysis
Variable Name in the Data Set
Description
(See the data dictionary for describing the variables.)
Type of Variable
(Qualitative or Quantitative)
Variable 1: “Income”
Annual household income in USD.
Quantitative
Variable 2: “Family Size”
Total Number of People in Family (Both Adults and Children)
Quantitative
Variable 3: “Annual Expenditure”
Total Amount of Annual Expenditures in USD
Quantitative
Variable 4: “Food”
Total Amount of Annual Expenditure on Food in USD
Quantitative
Variable 5: “Entertainment”
Total Amount of Annual Expenditure on Entertainment in USD
Quantitative
Reason(s) for Selecting the Variables and Expected Outcome(s):
1. 1. Variable 1: “Income” – Help to determine the total amount the family has before spending.
2. 2. Variable 2: “Family size” – Helps to determine whether big or small families have more expenditure.
3. 3. Variable 3: “Annual Expenditure” – It gives the total expenditure of the families given.
4. 4. Variable 4: “Food” – It shows the total amount families spend on food. It will ease comparison of food expenditure between families.
5. 5. Variable 5: “Entertainment” – It shows the amount spends on entertainment. It can lead to determination of luxurious families.
Data Set Description:
The data used in this study contains income, family size, annual expenditure, food and entertainment. Income, annual expenditure, food and entertainment are all continuous variables reporting income and expenditures in US dollars.
Proposed Data Analysis:
Measures of Central Tendency and Dispersion
Complete Table 2. Numerical Summaries of the Selected Variables and briefly explain why you choose those measurements. Note: The information for the required variable, “Income,” has already been completed and can be used as a guide for completing information on the remaining variables.
Table 2. Numerical Summaries of the Selected Variables
Variable Name
Measures of Central Tendency and Dispersion
Rationale for Why Appropriate
Variable 1:
“Income”
· ● Number of Observations
· ● Median
· ● Sample Standard Deviation
I am using median for two reasons:
1. 1. If there are any outliers or the data is not normally distributed, the median is the best measure of central tendency.
2. 2. The variable is quantitative.
I am using sample standard deviation for three reasons:
1. 1. The data is a sample from a larger data set.
2. 2. It is the most commonly used measure of dispersion.
3. 3. ...
STAT200 Assignment #1 - Descriptive Statistics Analysis Plan - Te.docx
STAT200: Assignment #1 - Descriptive Statistics Analysis Plan - Template
Page 1 of 3
University of Maryland University College
STAT200 - Assignment #1: Descriptive Statistics Data Analysis Plan
Identifying Information
Student (Full Name):
Class:
Instructor:
Date:
Scenario: Please write a few lines describing your scenario and the four variables (in addition to income) you have selected.
Use Table 1 to report the variables selected for this assignment. Note: The information for the required variable, “Income,” has already been completed and can be used as a guide for completing information on the remaining variables.
Table 1. Variables Selected for the Analysis
Variable Name in the Data Set
Description
(See the data dictionary for describing the variables.)
Type of Variable
(Qualitative or Quantitative)
Variable 1: “Income”
Annual household income in USD.
Quantitative
Variable 2:
Variable 3:
Variable 4:
Variable 5:
Reason(s) for Selecting the Variables and Expected Outcome(s):
Variable 1: “Income” -
Variable 2: “ “ -
Variable 3: “ “ -
Variable 4: “ “ -
Variable 5: “ “ -
Data Set Description:
Proposed Data Analysis:
Measures of Central Tendency and Dispersion
Complete Table 2. Numerical Summaries of the Selected Variables and briefly explain why you choose those measurements. Note: The information for the required variable, “Income,” has already been completed and can be used as a guide for completing information on the remaining variables.
Table 2. Numerical Summaries of the Selected Variables
Variable Name
Measures of Central Tendency and Dispersion
Rationale for Why Appropriate
Variable 1:
“Income”
Number of ObservationsMedianSample Standard Deviation
I am using median for two reasons:If there are any outliers or the data is not normally distributed, the median is the best measure of central tendency.The variable is quantitative.
I am using sample standard deviation for three reasons:The data is a sample from a larger data set.It is the most commonly used measure of dispersion.The variable is quantitative.
Variable 2:
Variable 3:
Variable 4:
Variable 5:
Graphs and/or Tables
Complete Table 3. Type of Graphs and/or Table for Selected Variables and briefly explain why you choose those graphs and/or tables. Note: The information for the required variable, “Income,” has already been completed and can be used as a guide for completing information on the remaining variables.
Table 3. Type of Graphs and/or Tables for Selected Variables
Variable Name
Graph and/or Table
Rationale for why Appropriate?
Variable 1:
“Income”
Graph: I will use the histogram to show the normal distribution of data.
Histogram is one of the best plot to show the normal distribution of quantitative level data .
Variable 2:
Variable 3:
Variable 4:
Variable 5:
STAT200: Written Assignment #1 - Descriptive Statistics Data Analysis Plan - Instructions
Page 1 of 4
STAT200 Introduction to Statistics
Assig.
STAT200 Introduction to Statistics Dataset for Written Assig.docx
STAT200 Introduction to Statistics
Dataset for Written Assignments
Description of Dataset:
The data is a random sample from the US Department of Labor’s 2016 Consumer Expenditure Surveys (CE) and provides information about the
composition of households and their annual expenditures (https://www.bls.gov/cex/). It contains information from 30 households, where a survey
responder provided the requested information; it is all self-reported information. This dataset contains four socioeconomic variables (whose names start
with SE) and four expenditure variables (whose names start with USD).
Description of Variables/Data Dictionary:
The following table is a data dictionary that describes the variables and their locations in this dataset (Note: Dataset is on second page of this document):
Variable Name Location in Dataset Variable Description Coding
UniqueID# First Column Unique number used to identify each survey
responder
Each responder has a unique
number from 1-30
SE-MaritalStatus Second Column Marital Status of Head of Household Not Married/Married
SE-Income Third Column Annual Household Income Amount in US Dollars
SE-AgeHeadHousehold Fourth Column Age of the Head of Household Age in Years
SE-FamilySize Fifth Column Total Number of People in Family (Both Adults
and Children)
Number of People in Family
USD-Annual Expenditures Sixth Column Total Amount of Annual Expenditures Amount in US Dollars
USD-Housing Seventh Column Total Amount of Annual Expenditure on Housing Amount in US Dollars
USD-Electricity Eighth Column Total Amount of Annual Expenditure on
Electricity
Amount in US Dollars
USD-Water Ninth Column Total Amount of Annual Expenditure on Water Amount in US Dollars
How to read the data set: Each row contains information from one household. For instance, the first row of the dataset starting on the next page shows
us that: the head of household is not married and is 53 years old, has an annual household income of $97,681, a family size of 4, annual expenditures of
$56,124, and spends $18,676 on housing, $1,468 on electricity, and $551 on water.
https://www.bls.gov/cex/
UniqueID# SE-MaritalStatus SE-Income SE-AgeHeadHousehold SE-FamilySize USD-AnnualExpenditures USD-Housing USD-Electricity USD-Water
1 Not Married 97681 53 4 56124 18676 1468 551
2 Not Married 96727 39 2 56440 18376 1441 542
3 Not Married 95432 51 1 55120 18391 1458 548
4 Not Married 96928 43 3 55932 18701 1479 520
5 Not Married 94929 59 2 55247 18483 1451 546
6 Not Married 95744 52 4 55963 18435 1465 555
7 Not Married 95366 48 2 57082 18576 1478 538
8 Not Married 96697 49 2 56453 18520 1469 545
9 Not Married 96572 59 2 56515 18648 1480 552
10 Not Married 96653 51 4 56488 18838 1470 535
11 Not Married 96664 53 3 55558 18502 1478 553
12 Not Married 96621 54 2 55746 18149 1455 540
13 Not Married 96886 44 2 55321 18312 1450 523
14 Not Married 96244 56 4 56051 18484 1457 539
15 Not Married 94867 60 1 55512 .
STAT200 Assignment #2 - Descriptive Statistics Analysis and.docx
STAT200: Assignment #2 - Descriptive Statistics Analysis and Writeup - Instructions
Page 1 of 3
STAT200 Introduction to Statistics
Assignment #2: Descriptive Statistics Analysis and Writeup
Assignment #2: Descriptive Statistics Analysis and Writeup
In the first assignment (Assignment #1: Descriptive Statistics Analysis Data Plan), you developed a
scenario about annual household expenditures and a plan for analyzing the data using descriptive
statistic methods. The purpose of this assignment is to carry out the descriptive statistics analysis plan
and write up the results. The expected outcome of this assignment is a two to three page write-up of
the findings from your analysis as well as a recommendation.
Assignment Steps:
Step #1: Review Feedback from Your Instructor
Before performing any analysis, please make sure to review your instructor’s feedback on Assignment
#1: Descriptive Statistics Data Analysis Plan. Based on the feedback, modify variables, tables, and
selected statistics, graphs, and tables, if needed.
Step #2: Perform Descriptive Statistic Analysis
Task 1: Look at the dataset.
• (Re)Familiarize yourself with the variables. Review Table 1: Variables Selected for the
Analysis you generated for the first assignment as well as your instructor’s feedback. In
addition, look at the data dictionary contained in the data set for information about the
variables.
• Select the variables you need for the analysis.
Task 2: Complete your data analysis, as outlined in your first assignment, with any needed
modifications, based on your instructor’s feedback.
• Calculate Measures of Central Tendency and Variability. Use the information from
Assignment #1 - Table 2. Numerical Summaries of the Selected Variables. Here again,
be sure to see your instructor’s feedback and incorporate into the analysis.
• Prepare Graphs and/or Tables. Use the information from Assignment #1 - Table 3.
Type of Graphs and/or Tables for Selected Variables. Here again, be sure to see your
instructor’s feedback and incorporate into the analysis.
STAT200: Assignment #2 - Descriptive Statistics Analysis and Writeup - Instructions
Page 2 of 3
Step #3: Write-up findings using the Provided Template
For this part of the assignment, write a short 2-3 page write-up of the process you followed and the
findings from your analysis. You will describe, in words, the statistical analysis used and present the
results in both statistical/text and graphic formats.
Here are the main sections for this assignment:
✓ Identifying Information. Fill in information on name, class, instructor, and date.
✓ Introduction. For this section, use the same scenario you submitted for the first assignment and
modified using your instructor’s feedback, if needed. Include Table 1 (Table 1: Variables
Selected for the Analysis) you used in Assignment #1 to show the variables you selected for the
analysis.
✓ Data .
Dataset for Written AssignmentsDescription of DatasetThe .docx
Dataset for Written Assignments
Description of Dataset:
The data is a random sample that provides information about the composition of households and their annual expenditures. It contains information from 30 households, where a survey responder provided the requested information; it is all self-reported information. This dataset contains four socioeconomic variables (whose names start with SE) and four expenditure variables (whose names start with USD).
Description of Variables/Data Dictionary:
The following table is a data dictionary that describes the variables and their locations in this dataset (Note: Dataset is on second page of this document):
Variable Name
Location in Dataset
Variable Description
Coding
UniqueID#
First Column
Unique number used to identify each survey responder
Each responder has a unique number from 1-30
SE-MaritalStatus
Second Column
Marital Status of Head of Household
Not Married/Married
SE-Income
Third Column
Annual Household Income
Amount in US Dollars
SE-AgeHeadHousehold
Fourth Column
Age of the Head of Household
Age in Years
SE-FamilySize
Fifth Column
Total Number of People in Family (Both Adults and Children)
Number of People in Family
USD-Annual Expenditures
Sixth Column
Total Amount of Annual Expenditures
Amount in US Dollars
USD-Housing
Seventh Column
Total Amount of Annual Expenditure on Housing
Amount in US Dollars
USD-Electricity
Eighth Column
Total Amount of Annual Expenditure on Electricity
Amount in US Dollars
USD-Water
Ninth Column
Total Amount of Annual Expenditure on Water
Amount in US Dollars
How to read the data set: Each row contains information from one household. For instance, the first row of the dataset starting on the next page shows us that: the head of household is not married and is 59 years old, has an annual household income of $94,929, a family size of 2, annual expenditures of $55,247, and spends $18,483 on housing, $1,451 on electricity, and $546 on water.
UniqueID#
SE-MaritalStatus
SE-income
SE-AgeHeadHousehold
SE-FamilySize
USD-AnnualExpenditures
USD-Housing
USD-Electricity
USD-Water
1
Not Married
94929
59
2
55247
18483
1451
546
2
Not Married
96621
54
2
55746
18149
1455
540
3
Not Married
96664
53
3
55558
18502
1478
553
4
Not Married
96522
43
4
56152
18483
1457
537
5
Not Married
96697
49
2
56453
18520
1469
545
6
Not Married
96727
39
2
56440
18376
1441
542
7
Not Married
94867
60
1
55512
18633
1485
523
8
Not Married
96690
57
2
56097
18334
1453
535
9
Not Married
97469
35
4
54929
18514
1451
565
10
Not Married
96886
44
2
55321
18312
1450
523
11
Not Married
95744
52
4
55963
18435
1465
555
12
Not Married
96572
59
2
56515
18648
1480
552
13
Not Married
95366
48
2
57082
18576
1478
538
14
Not Married
97912
49
1
55704
18619
1450
553
15
Not Married
96928
43
3
55932
18701
1479
520
16
Married
114051
42
5
84486
25728
1452
818
17
Married
106627
56
3
82676
22414
1688
709
18
Married
109312
37
6
80801
25392
1514
743
19
Married
103144
29
5
75393
26322
1386
626
20
Married
111195
30
5
80865
25018
14.
Recommended
STAT200 Assignment #2 - Descriptive Statistics Analysis Write.docx
STAT200: Assignment #2 - Descriptive Statistics Analysis Writeup - Template
Page 1 of 3
University of Maryland University College
STAT200 - Assignment #2: Descriptive Statistics Analysis and Writeup
Identifying Information
Student (Full Name):
Class:
Instructor:
Date:
Introduction:
Use the same scenario you submitted for the first assignment with modifications using your instructor’s
feedback, if needed. Include Table 1: Variables Selected for the Analysis you used in Assignment #1 to
show the variables you selected for analysis.
Table 1. Variables Selected for the Analysis
Variable Name in data
set
Description Type of Variable (Qualitative or
Quantitative)
Variable 1: “Income”
Annual household income in
USD.
Quantitative
Variable 2:
Variable 3:
Variable 4:
Variable 5:
Data Set Description and Method Used for Analysis:
Results:
Variable 1: Income
Numerical Summary.
STAT200: Assignment #2 - Descriptive Statistics Analysis Writeup - Template
Page 2 of 3
Table 2. Descriptive Analysis for Variable 1
Variable n Measure(s) of Central Tendency Measure(s) of Dispersion
Variable: Income Median= SD =
Graph and/or Table: Histogram of Income
(Place Histogram here)
Description of Findings.
Variable 2: (Fill in name of variable)
Numerical Summary.
Table 3. Descriptive Analysis for Variable 2
Variable n Measure(s) of Central Tendency Measure(s) of Dispersion
Variable:
Graph and/or Table.
(Place Graph or Table Here)
Description of Findings.
Variable 3: (Fill in name of variable)
Numerical Summary.
Table 4. Descriptive Analysis for Variable 3
Variable n Measure(s) of Central Tendency Measure(s) of Dispersion
Variable:
Graph and/or Table.
(Place Graph or Table Here)
STAT200: Assignment #2 - Descriptive Statistics Analysis Writeup - Template
Page 3 of 3
Description of Findings.
Variable 4: (Fill in name of variable)
Numerical Summary.
Table 5. Descriptive Analysis for Variable 4
Variable N Mean/Median St. Dev.
Variable 4:
Graph and/or Table.
(Place Graph or Table Here)
Description of Findings.
Variable 5: (Fill in name of variable)
Numerical Summary.
Table 6. Descriptive Analysis for Variable 5
Variable n Measure(s) of Central Tendency Measure(s) of Dispersion
Variable:
Graph and/or Table.
(Place Graph or Table Here)
Description of Findings.
Discussion and Conclusion.
Briefly discuss each variable in the same sequence as presented in the results. What has the highest
expenditure? What variable has the lowest expenditure? If you were to recommend a place to save
money, which expenditure would it be and why? Note: The section should be no more than 2
paragraphs.
STAT200 Introduction to Statistics
Dataset for Written Assignments
Description of Dataset:
The data is a random sample from the US Department of Labor’s 2016 Consumer Expenditure Surveys.
STAT200 Assignment #2 - Descriptive Statistics Analysis Writeup -.docx
STAT200: Assignment #2 - Descriptive Statistics Analysis Writeup - Template
Page 3 of 3
University of Maryland University College
STAT200 - Assignment #2: Descriptive Statistics Analysis and Writeup
Identifying Information
Student (Full Name):
Class: STAT 200
Instructor:
Date:
Introduction:
Use the same scenario you submitted for the first assignment with modifications using your instructor’s feedback, if needed. Include Table 1: Variables Selected for the Analysis you used in Assignment #1 to show the variables you selected for analysis.
Table 1. Variables Selected for the Analysis
Variable Name in data set
Description
Type of Variable (Qualitative or Quantitative)
Variable 1: “Income”
Annual household income in USD.
Quantitative
Variable 2: “Marital Status”
Martial Status as the Head of Household
Qualitative
Variable 3: “Family Size”
Total number of people in the house to include adults and children
Quantitative
Variable 4: “Annual Expenditures”
Total amount of annual expenditures
Quantitative
Variable 5: “Age Head of Household”
Age of Head of Household
Quantitative
Data Set Description and Method Used for Analysis:
Results:
Variable 1: Income
Numerical Summary.
Table 2. Descriptive Analysis for Variable 1
Variable
n
Measure(s) of Central Tendency
Measure(s) of Dispersion
Variable: Income
Median=
SD =
Graph and/or Table: Histogram of Income
(Place Histogram here)
Description of Findings.
Variable 2: (Fill in name of variable)
Numerical Summary.
Table 3. Descriptive Analysis for Variable 2
Variable
n
Measure(s) of Central Tendency
Measure(s) of Dispersion
Variable:
Graph and/or Table.
(Place Graph or Table Here)
Description of Findings.
Variable 3: (Fill in name of variable)
Numerical Summary.
Table 4. Descriptive Analysis for Variable 3
Variable
n
Measure(s) of Central Tendency
Measure(s) of Dispersion
Variable:
Graph and/or Table.
(Place Graph or Table Here)
Description of Findings.
Variable 4: (Fill in name of variable)
Numerical Summary.
Table 5. Descriptive Analysis for Variable 4
Variable
N
Mean/Median
St. Dev.
Variable 4:
Graph and/or Table.
(Place Graph or Table Here)
Description of Findings.
Variable 5: (Fill in name of variable)
Numerical Summary.
Table 6. Descriptive Analysis for Variable 5
Variable
n
Measure(s) of Central Tendency
Measure(s) of Dispersion
Variable:
Graph and/or Table.
(Place Graph or Table Here)
Description of Findings.
Discussion and Conclusion.
Briefly discuss each variable in the same sequence as presented in the results. What has the highest expenditure? What variable has the lowest expenditure? If you were to recommend a place to save money, which expenditure would it be and why? Note: The section should be no more than 2 paragraphs.
STAT200 Introduction to Statistics
Dataset for Written Assignments
Description of Dataset:
The data is a random sample from the US Department of Labor’s 2016 Consumer Expenditure Surveys (CE) and provides informat.
STAT200 Introduction to StatisticsDataset for Written Assignment.docx
STAT200 Introduction to Statistics
Dataset for Written Assignments
Description of Dataset:
The data is a random sample from the US Department of Labor’s 2016 Consumer Expenditure Surveys (CE) and provides information about the composition of households and their annual expenditures (https://www.bls.gov/cex/). It contains information from 30 households, where a survey responder provided the requested information; it is all self-reported information. This dataset contains four socioeconomic variables (whose names start with SE) and four expenditure variables (whose names start with USD).
Description of Variables/Data Dictionary:
The following table is a data dictionary that describes the variables and their locations in this dataset (Note: Dataset is on second page of this document):
Variable Name
Location in Dataset
Variable Description
Coding
UniqueID#
First Column
Unique number used to identify each survey responder
Each responder has a unique number from 1-30
SE-MaritalStatus
Second Column
Marital Status of Head of Household
Not Married/Married
SE-Income
Third Column
Annual Household Income
Amount in US Dollars
SE-AgeHeadHousehold
Fourth Column
Age of the Head of Household
Age in Years
SE-FamilySize
Fifth Column
Total Number of People in Family (Both Adults and Children)
Number of People in Family
USD-Annual Expenditures
Sixth Column
Total Amount of Annual Expenditures
Amount in US Dollars
USD-Food
Seventh Column
Total Amount of Annual Expenditure on Food
Amount in US Dollars
USD-Entertainment
Eighth Column
Total Amount of Annual Expenditure on Entertainment
Amount in US Dollars
USD-Education
Ninth Column
Total Amount of Annual Expenditure on Education
Amount in US Dollars
How to read the data set: Each row contains information from one household. For instance, the first row of the dataset starting on the next page shows us that: the head of household is not married and is 40 years old, has an annual household income of $98,717, a family size of 3, annual expenditures of $56,393, and spends $7,036 on food, $106 on entertainment, and $213 on education.
UniqueID#
SE-MaritalStatus
SE-Income
SE-AgeHeadHousehold
SE-FamilySize
USD-AnnualExpenditures
USD-Food
USD-Entertainment
USD-Education
1
Not Married
98717
40
3
56393
7036
106
213
2
Not Married
96572
59
2
56515
7179
95
349
3
Not Married
96690
57
2
56097
6822
88
252
4
Not Married
96664
53
3
55558
7051
83
295
5
Not Married
96886
44
2
55321
6982
79
312
6
Not Married
96522
43
4
56152
6991
101
237
7
Not Married
97912
49
1
55704
6937
97
277
8
Not Married
96727
39
2
56440
7051
93
222
9
Not Married
96928
43
3
55932
6953
105
273
10
Not Married
95744
52
4
55963
7040
105
340
11
Not Married
97681
53
4
56124
7097
108
263
12
Not Married
95432
51
1
55120
7089
84
274
13
Not Married
94929
59
2
55247
6948
97
236
14
Not Married
96621
54
2
55746
7000
106
322
15
Not Married
95366
48
2
57082
7130
90
305
16
Married
101829
45
4
82385
10821
201
810
17
Married
98309
51
2
75776
9118
117
477
18
Married
112559
39
3
80.
5University of Maryland University CollegeSTAT200 - Assignm.docx
5
University of Maryland University College
STAT200 - Assignment #1: Descriptive Statistics Data Analysis Plan
Identifying Information
Amber Wilson
Stat 200 6755
Dr.Barnes
11/4/19
Scenario:
I am a student conducting a research to determine the main factors contributing expenditures of a given family. Data given provide information on income, expenditure on food, family size, annual expenditure and expenditure on entertainment.
The selected variables are shown in the table below.
Table 1. Variables Selected for the Analysis
Variable Name in the Data Set
Description
(See the data dictionary for describing the variables.)
Type of Variable
(Qualitative or Quantitative)
Variable 1: “Income”
Annual household income in USD.
Quantitative
Variable 2: “Family Size”
Total Number of People in Family (Both Adults and Children)
Quantitative
Variable 3: “Annual Expenditure”
Total Amount of Annual Expenditures in USD
Quantitative
Variable 4: “Food”
Total Amount of Annual Expenditure on Food in USD
Quantitative
Variable 5: “Entertainment”
Total Amount of Annual Expenditure on Entertainment in USD
Quantitative
Reason(s) for Selecting the Variables and Expected Outcome(s):
1. 1. Variable 1: “Income” – Help to determine the total amount the family has before spending.
2. 2. Variable 2: “Family size” – Helps to determine whether big or small families have more expenditure.
3. 3. Variable 3: “Annual Expenditure” – It gives the total expenditure of the families given.
4. 4. Variable 4: “Food” – It shows the total amount families spend on food. It will ease comparison of food expenditure between families.
5. 5. Variable 5: “Entertainment” – It shows the amount spends on entertainment. It can lead to determination of luxurious families.
Data Set Description:
The data used in this study contains income, family size, annual expenditure, food and entertainment. Income, annual expenditure, food and entertainment are all continuous variables reporting income and expenditures in US dollars.
Proposed Data Analysis:
Measures of Central Tendency and Dispersion
Complete Table 2. Numerical Summaries of the Selected Variables and briefly explain why you choose those measurements. Note: The information for the required variable, “Income,” has already been completed and can be used as a guide for completing information on the remaining variables.
Table 2. Numerical Summaries of the Selected Variables
Variable Name
Measures of Central Tendency and Dispersion
Rationale for Why Appropriate
Variable 1:
“Income”
· ● Number of Observations
· ● Median
· ● Sample Standard Deviation
I am using median for two reasons:
1. 1. If there are any outliers or the data is not normally distributed, the median is the best measure of central tendency.
2. 2. The variable is quantitative.
I am using sample standard deviation for three reasons:
1. 1. The data is a sample from a larger data set.
2. 2. It is the most commonly used measure of dispersion.
3. 3. ...
STAT200 Assignment #1 - Descriptive Statistics Analysis Plan - Te.docx
STAT200: Assignment #1 - Descriptive Statistics Analysis Plan - Template
Page 1 of 3
University of Maryland University College
STAT200 - Assignment #1: Descriptive Statistics Data Analysis Plan
Identifying Information
Student (Full Name):
Class:
Instructor:
Date:
Scenario: Please write a few lines describing your scenario and the four variables (in addition to income) you have selected.
Use Table 1 to report the variables selected for this assignment. Note: The information for the required variable, “Income,” has already been completed and can be used as a guide for completing information on the remaining variables.
Table 1. Variables Selected for the Analysis
Variable Name in the Data Set
Description
(See the data dictionary for describing the variables.)
Type of Variable
(Qualitative or Quantitative)
Variable 1: “Income”
Annual household income in USD.
Quantitative
Variable 2:
Variable 3:
Variable 4:
Variable 5:
Reason(s) for Selecting the Variables and Expected Outcome(s):
Variable 1: “Income” -
Variable 2: “ “ -
Variable 3: “ “ -
Variable 4: “ “ -
Variable 5: “ “ -
Data Set Description:
Proposed Data Analysis:
Measures of Central Tendency and Dispersion
Complete Table 2. Numerical Summaries of the Selected Variables and briefly explain why you choose those measurements. Note: The information for the required variable, “Income,” has already been completed and can be used as a guide for completing information on the remaining variables.
Table 2. Numerical Summaries of the Selected Variables
Variable Name
Measures of Central Tendency and Dispersion
Rationale for Why Appropriate
Variable 1:
“Income”
Number of ObservationsMedianSample Standard Deviation
I am using median for two reasons:If there are any outliers or the data is not normally distributed, the median is the best measure of central tendency.The variable is quantitative.
I am using sample standard deviation for three reasons:The data is a sample from a larger data set.It is the most commonly used measure of dispersion.The variable is quantitative.
Variable 2:
Variable 3:
Variable 4:
Variable 5:
Graphs and/or Tables
Complete Table 3. Type of Graphs and/or Table for Selected Variables and briefly explain why you choose those graphs and/or tables. Note: The information for the required variable, “Income,” has already been completed and can be used as a guide for completing information on the remaining variables.
Table 3. Type of Graphs and/or Tables for Selected Variables
Variable Name
Graph and/or Table
Rationale for why Appropriate?
Variable 1:
“Income”
Graph: I will use the histogram to show the normal distribution of data.
Histogram is one of the best plot to show the normal distribution of quantitative level data .
Variable 2:
Variable 3:
Variable 4:
Variable 5:
STAT200: Written Assignment #1 - Descriptive Statistics Data Analysis Plan - Instructions
Page 1 of 4
STAT200 Introduction to Statistics
Assig.
STAT200 Introduction to Statistics Dataset for Written Assig.docx
STAT200 Introduction to Statistics
Dataset for Written Assignments
Description of Dataset:
The data is a random sample from the US Department of Labor’s 2016 Consumer Expenditure Surveys (CE) and provides information about the
composition of households and their annual expenditures (https://www.bls.gov/cex/). It contains information from 30 households, where a survey
responder provided the requested information; it is all self-reported information. This dataset contains four socioeconomic variables (whose names start
with SE) and four expenditure variables (whose names start with USD).
Description of Variables/Data Dictionary:
The following table is a data dictionary that describes the variables and their locations in this dataset (Note: Dataset is on second page of this document):
Variable Name Location in Dataset Variable Description Coding
UniqueID# First Column Unique number used to identify each survey
responder
Each responder has a unique
number from 1-30
SE-MaritalStatus Second Column Marital Status of Head of Household Not Married/Married
SE-Income Third Column Annual Household Income Amount in US Dollars
SE-AgeHeadHousehold Fourth Column Age of the Head of Household Age in Years
SE-FamilySize Fifth Column Total Number of People in Family (Both Adults
and Children)
Number of People in Family
USD-Annual Expenditures Sixth Column Total Amount of Annual Expenditures Amount in US Dollars
USD-Housing Seventh Column Total Amount of Annual Expenditure on Housing Amount in US Dollars
USD-Electricity Eighth Column Total Amount of Annual Expenditure on
Electricity
Amount in US Dollars
USD-Water Ninth Column Total Amount of Annual Expenditure on Water Amount in US Dollars
How to read the data set: Each row contains information from one household. For instance, the first row of the dataset starting on the next page shows
us that: the head of household is not married and is 53 years old, has an annual household income of $97,681, a family size of 4, annual expenditures of
$56,124, and spends $18,676 on housing, $1,468 on electricity, and $551 on water.
https://www.bls.gov/cex/
UniqueID# SE-MaritalStatus SE-Income SE-AgeHeadHousehold SE-FamilySize USD-AnnualExpenditures USD-Housing USD-Electricity USD-Water
1 Not Married 97681 53 4 56124 18676 1468 551
2 Not Married 96727 39 2 56440 18376 1441 542
3 Not Married 95432 51 1 55120 18391 1458 548
4 Not Married 96928 43 3 55932 18701 1479 520
5 Not Married 94929 59 2 55247 18483 1451 546
6 Not Married 95744 52 4 55963 18435 1465 555
7 Not Married 95366 48 2 57082 18576 1478 538
8 Not Married 96697 49 2 56453 18520 1469 545
9 Not Married 96572 59 2 56515 18648 1480 552
10 Not Married 96653 51 4 56488 18838 1470 535
11 Not Married 96664 53 3 55558 18502 1478 553
12 Not Married 96621 54 2 55746 18149 1455 540
13 Not Married 96886 44 2 55321 18312 1450 523
14 Not Married 96244 56 4 56051 18484 1457 539
15 Not Married 94867 60 1 55512 .
STAT200 Assignment #2 - Descriptive Statistics Analysis and.docx
STAT200: Assignment #2 - Descriptive Statistics Analysis and Writeup - Instructions
Page 1 of 3
STAT200 Introduction to Statistics
Assignment #2: Descriptive Statistics Analysis and Writeup
Assignment #2: Descriptive Statistics Analysis and Writeup
In the first assignment (Assignment #1: Descriptive Statistics Analysis Data Plan), you developed a
scenario about annual household expenditures and a plan for analyzing the data using descriptive
statistic methods. The purpose of this assignment is to carry out the descriptive statistics analysis plan
and write up the results. The expected outcome of this assignment is a two to three page write-up of
the findings from your analysis as well as a recommendation.
Assignment Steps:
Step #1: Review Feedback from Your Instructor
Before performing any analysis, please make sure to review your instructor’s feedback on Assignment
#1: Descriptive Statistics Data Analysis Plan. Based on the feedback, modify variables, tables, and
selected statistics, graphs, and tables, if needed.
Step #2: Perform Descriptive Statistic Analysis
Task 1: Look at the dataset.
• (Re)Familiarize yourself with the variables. Review Table 1: Variables Selected for the
Analysis you generated for the first assignment as well as your instructor’s feedback. In
addition, look at the data dictionary contained in the data set for information about the
variables.
• Select the variables you need for the analysis.
Task 2: Complete your data analysis, as outlined in your first assignment, with any needed
modifications, based on your instructor’s feedback.
• Calculate Measures of Central Tendency and Variability. Use the information from
Assignment #1 - Table 2. Numerical Summaries of the Selected Variables. Here again,
be sure to see your instructor’s feedback and incorporate into the analysis.
• Prepare Graphs and/or Tables. Use the information from Assignment #1 - Table 3.
Type of Graphs and/or Tables for Selected Variables. Here again, be sure to see your
instructor’s feedback and incorporate into the analysis.
STAT200: Assignment #2 - Descriptive Statistics Analysis and Writeup - Instructions
Page 2 of 3
Step #3: Write-up findings using the Provided Template
For this part of the assignment, write a short 2-3 page write-up of the process you followed and the
findings from your analysis. You will describe, in words, the statistical analysis used and present the
results in both statistical/text and graphic formats.
Here are the main sections for this assignment:
✓ Identifying Information. Fill in information on name, class, instructor, and date.
✓ Introduction. For this section, use the same scenario you submitted for the first assignment and
modified using your instructor’s feedback, if needed. Include Table 1 (Table 1: Variables
Selected for the Analysis) you used in Assignment #1 to show the variables you selected for the
analysis.
✓ Data .
Dataset for Written AssignmentsDescription of DatasetThe .docx
Dataset for Written Assignments
Description of Dataset:
The data is a random sample that provides information about the composition of households and their annual expenditures. It contains information from 30 households, where a survey responder provided the requested information; it is all self-reported information. This dataset contains four socioeconomic variables (whose names start with SE) and four expenditure variables (whose names start with USD).
Description of Variables/Data Dictionary:
The following table is a data dictionary that describes the variables and their locations in this dataset (Note: Dataset is on second page of this document):
Variable Name
Location in Dataset
Variable Description
Coding
UniqueID#
First Column
Unique number used to identify each survey responder
Each responder has a unique number from 1-30
SE-MaritalStatus
Second Column
Marital Status of Head of Household
Not Married/Married
SE-Income
Third Column
Annual Household Income
Amount in US Dollars
SE-AgeHeadHousehold
Fourth Column
Age of the Head of Household
Age in Years
SE-FamilySize
Fifth Column
Total Number of People in Family (Both Adults and Children)
Number of People in Family
USD-Annual Expenditures
Sixth Column
Total Amount of Annual Expenditures
Amount in US Dollars
USD-Housing
Seventh Column
Total Amount of Annual Expenditure on Housing
Amount in US Dollars
USD-Electricity
Eighth Column
Total Amount of Annual Expenditure on Electricity
Amount in US Dollars
USD-Water
Ninth Column
Total Amount of Annual Expenditure on Water
Amount in US Dollars
How to read the data set: Each row contains information from one household. For instance, the first row of the dataset starting on the next page shows us that: the head of household is not married and is 59 years old, has an annual household income of $94,929, a family size of 2, annual expenditures of $55,247, and spends $18,483 on housing, $1,451 on electricity, and $546 on water.
UniqueID#
SE-MaritalStatus
SE-income
SE-AgeHeadHousehold
SE-FamilySize
USD-AnnualExpenditures
USD-Housing
USD-Electricity
USD-Water
1
Not Married
94929
59
2
55247
18483
1451
546
2
Not Married
96621
54
2
55746
18149
1455
540
3
Not Married
96664
53
3
55558
18502
1478
553
4
Not Married
96522
43
4
56152
18483
1457
537
5
Not Married
96697
49
2
56453
18520
1469
545
6
Not Married
96727
39
2
56440
18376
1441
542
7
Not Married
94867
60
1
55512
18633
1485
523
8
Not Married
96690
57
2
56097
18334
1453
535
9
Not Married
97469
35
4
54929
18514
1451
565
10
Not Married
96886
44
2
55321
18312
1450
523
11
Not Married
95744
52
4
55963
18435
1465
555
12
Not Married
96572
59
2
56515
18648
1480
552
13
Not Married
95366
48
2
57082
18576
1478
538
14
Not Married
97912
49
1
55704
18619
1450
553
15
Not Married
96928
43
3
55932
18701
1479
520
16
Married
114051
42
5
84486
25728
1452
818
17
Married
106627
56
3
82676
22414
1688
709
18
Married
109312
37
6
80801
25392
1514
743
19
Married
103144
29
5
75393
26322
1386
626
20
Married
111195
30
5
80865
25018
14.
001
The document discusses introductory statistics concepts including descriptive statistics, inferential statistics, types of variables, levels of measurement, frequency tables, histograms, and other methods for organizing and presenting data. Chapter 1 covers what statistics is, types of statistics, variables, and levels of measurement. Chapter 2 discusses describing data through frequency tables, bar charts, histograms, and other graphs. The learning goals are to understand descriptive vs inferential statistics and distinguish between different statistical concepts.
Research methodology - Analysis of Data
Processing & Analysis of Data, Data editing, Benefits of data editing, Data coding, Classification of data, CLASSIFICATION ACCORDING THE ATTRIBUTES, CLASSIFICATION ON THE BASIS OF INTERVAL, TABULATION of data, Types of tables, Graphing of data, Bar chart, Pie chart, Line graph, histogram, Polygon / ogive, Analysis of Data, Descriptive Analysis, Uni-Variate Analysis, Bivariate Analysis, Multi-Variate Analysis, Causal Analysis, Inferential Analysis, PARAMETRIC TESTS, Non parametric Test,
General Statistics boa
The document contains an outline of the table of contents for a textbook on general statistics. It covers topics such as preliminary concepts, data collection and presentation, measures of central tendency, measures of dispersion and skewness, and permutations and combinations. Sample chapters discuss introduction to statistics, variables and data, methods of presenting data through tables, graphs and diagrams, computing the mean, median and mode, and other statistical measures.
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This document provides an overview of basic statistics concepts. It defines statistics as the science of collecting, presenting, analyzing, and reasonably interpreting data. Descriptive statistics are used to summarize and organize data through methods like tables, graphs, and descriptive values, while inferential statistics allow researchers to make general conclusions about populations based on sample data. Variables can be either categorical or quantitative, and their distributions and presentations are discussed.
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This document provides an overview of key concepts in statistics including:
- Descriptive statistics such as frequency distributions which organize and summarize data
- Inferential statistics which make estimates or predictions about populations based on samples
- Types of variables including quantitative, qualitative, discrete and continuous
- Levels of measurement including nominal, ordinal, interval and ratio
- Common measures of central tendency (mean, median, mode) and dispersion (range, standard deviation)
Elementary Statistics
credit to the authors:
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This document discusses descriptive statistics and numerical measures used to describe data sets. It introduces measures of central tendency including the mean, median, and mode. The mean is the average value calculated by summing all values and dividing by the number of values. The median is the middle value when values are arranged in order. The mode is the most frequently occurring value. The document also discusses measures of dispersion like range and standard deviation which describe how spread out the data is. Examples are provided to demonstrate calculating the mean, median and other descriptive statistics.
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This document discusses key concepts in statistics including data, variables, scales of measurement, descriptive statistics, statistical inference, and data sources. It provides examples of how statistical methods can be applied in business, finance, and economics. Descriptive statistics like frequencies, percentages, histograms, and numerical summaries are used to describe data from a sample of auto repair tune-ups. Statistical inference involves using a sample to make estimates about unknown population characteristics.
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This document discusses key concepts in statistics including data, variables, scales of measurement, descriptive statistics, statistical inference, and data sources. It provides examples of how statistical methods can be applied in economics, business, and finance. Descriptive statistics like frequency tables, histograms, and measures of central tendency are used to summarize sample data. Statistical inference involves using sample data to make estimates about population parameters.
Lecture 1.ppt
This document discusses key concepts in statistics including data, variables, scales of measurement, descriptive statistics, statistical inference, and data sources. It provides examples of how statistical methods can be applied in business, finance, and economics. Descriptive statistics like frequencies, percentages, histograms, and numerical summaries are used to characterize sample data. Statistical inference involves using sample data to make estimates about population characteristics.
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This document discusses key concepts in statistics including data, variables, scales of measurement, descriptive statistics, statistical inference, and data sources. It provides examples of how statistical methods can be applied in business, finance, and economics. Descriptive statistics like frequencies, percentages, histograms, and numerical summaries are used to describe data from a sample of auto repair tune-ups. Statistical inference involves using a sample to make estimates about unknown population characteristics.
Sheet1Number of Visits Per DayNumber of Status Changes Per WeekAge.docx
Sheet1Number of Visits Per DayNumber of Status Changes Per WeekAge5138VariableMeanMedianModeRangeVarianceStandard Deviation15527Visits Per Day5121Status Changes Per Week25319Age50525631881024Data from:http://www.statcrunch.com/5.0/index.php?dataid=48537311028331910120114210481032112715118207190040003015526417311219414110320302051325324511851205621301201512053411551933190049543111182120422000520027101013531841219511820194121211811218124202019101018501002230224532050142337205120113331841514102541547319402010019004215320412800401166103145220122910524005032173119206310018212125719152202020002533310025512021332024002000211021002750201031911195718213810002221211532600361010245018511942202149311884185126013220102131371551500561502000285656185136001421471053022211012061352511800422083200212223113715520514520719106211581120332128241328233810540522111122113522632370035108540013761181120104194120004800.52351012128458221911390033321973025114820532022211272514471043405030191111004535281424602019201529105192002010140052342620718212630321120231800401910520151721942221071910719305041200058362143102251237120215119332632193832721356301810519421832351128531931193810221822310127425820234339204183218321900532238105411007519424318102362020171022040283850100292121286143250232319101025121823198204219442831293218203451432143117021181031815418530202521825104010263120101952243325102201511930220114131171051944240065231920220121443015121531851193024757144246203210213125621920275121104319121725104626191048102581181167441643400556320452051182024474181001841192312562481932339525214210494810255132310561312191155013650100181152101910552224191039210043302500560136814151263020107323262260415152124303193061004758108180039103900550050315910322602048404411354020http://www.statcrunch.com/5.0/index.php?dataid=485373
Sheet2
Sheet3
PSYC 354
Excel Homework 3
(70 pts possible)
The objective of your third Excel assignment is to learn to describe a data set using measures of central tendency and variability. First, be sure you view the presentation that covers computing central tendency and variability in Excel found in the Reading & Study folder in Module/Week 3. This presentation goes through the steps you will need to be familiar with in order to complete this assignment.
In Module/Week 3, the goal is to use Excel formulas to calculate specific measures of central tendency and variability of a given data set, using the steps you learned during the presentation. Open “Data Set 3,” found in the Assignment Instructions folder, under “Excel Homework 3,” then follow the steps below to complete Module/Week 3’s assignment.
1. Research Question: In Module/Week 3, the data comes from an internet survey that assessed the frequency of use of the social networking site Facebook ™. A psychologist interested in time spent visiting a social networking site collected data from 366 respondents concerning: 1.) number of visits to FB per day; 2.) number of times participants changed FB “status” per w.
Lesson 002
This document provides a summary of key concepts from Chapter 3 of a statistics textbook, including:
- How to calculate measures of central tendency like the mean, median, mode, and weighted mean
- The characteristics and properties of each measure
- How the positions of the mean, median and mode relate to the shape of the distribution
- How to calculate the mean, median and mode for grouped data
- What the geometric mean represents and how it is calculated
Biostatistics
This document provides an introduction to biostatistics and statistical concepts. It discusses descriptive statistics, which are used to describe data through measures like mean, median and mode. Inferential statistics are used to make inferences about populations based on sample data. Key terms are also defined, such as parameter (a population characteristic), statistic (a quantity calculated from a sample), population (the entire group being studied), and sample (a subset of a population). The document also covers topics like frequency distributions, graphical representation of data through graphs and diagrams, and how to construct tables and frequency distributions.
STAT200 Assignment #3 - Inferential Statistics Analysis an.docx
STAT200: Assignment #3 - Inferential Statistics Analysis and Writeup - Instructions
Page 1 of 5
STAT200 Introduction to Statistics
Assignment #3: Inferential Statistics Analysis and Writeup
Purpose:
The purpose of this assignment is to develop and carry out an inferential statistics analysis plan and
write up the findings. There are two main parts to this assignment:
● Part A: Inferential Statistics Data Plan and Analysis
● Part B: Write up of Results
Part A: Prepare Data Plan, Analyze Data, and Complete Part A of the Assignment #3 Template
➢ Task 1: Select Variables. Review the variables you used for assignments #1 and #2. Select your
qualitative socioeconomic variable as your grouping variable and the two expenditure variables
from the variables used in these previous assignments. Fill in Table 1: Variables Selected for
Analysis with name, description, and type of variable (i.e., qualitative or quantitative).
➢ Task 2: Select and Run a One Sample Confidence Interval Analysis. For one expenditure
variable, select and run the appropriate method for estimating a parameter, based on a statistic
(i.e., confidence interval method). Complete Table 2: Confidence Interval Information and
Results, which follows the format outlined by Kozak and the course’s problem-solving approach,
including:
○ Random variable stated in words
○ Confidence interval method, including rationale and assumptions
○ Method used for analyzing data (i.e., web applets, Excel, TI calculator, etc.).
○ Results obtained
○ Interpretation
➢ Task 3: Select Two Sample Hypothesis Test. Using the second expenditure variable (with the
socioeconomic variable as the grouping variable), select and run the appropriate method for
making decisions about two parameters relative to observed statistics (i.e., two sample
STAT200: Assignment #3 - Inferential Statistics Analysis and Writeup - Instructions
Page 2 of 5
hypothesis test method). Complete Table 3: Two Sample Hypothesis Test Analysis, which
follows the format outlined by Kozak and the course’s problem-solving approach, including:
○ Hypotheses (null and alternative).
○ Two sample hypothesis testing method, including rationale and assumptions
○ Method used for analyzing data (i.e., web applets, Excel, TI calculator, etc.).
○ Results obtained.
○ Interpretation (i.e., Reject the null hypothesis OR Fail to reject null hypothesis)
Step 2: Write Up Results and Complete Part B of the Assignment #3 Template
For this 1 to 2 page section, refer to the inferential statistics data plan and computations done for Part A
of this assignment. Address the following area:
➢ Introduction. Based on the scenario you submitted for the second assignment, provide a brief
description of scenario, including the variables that were used in this analysis. Include a
completed “Table 1: Variables Selected for Analysis to show the variables you selected for
analysis.
.
Quatitative Data Analysis
This document provides an overview of quantitative data analysis. It discusses data preparation, descriptive statistics such as measures of central tendency and dispersion, inferential statistics, and interpretation of results. The key steps in quantitative analysis are described as data preparation, describing the data through descriptive statistics, drawing inferences through inferential statistics, and interpreting the findings. Common statistical techniques like mean, median, mode, standard deviation, and correlation are also summarized.
Basics of data_interpretation
This document provides information about data interpretation and different ways to present data. It discusses numerical data tables including time series tables, spatial tables, frequency distribution tables, and cumulative frequency tables. Examples are given to show how to calculate capacity utilization, sales growth percentages, and solve other problems using the data in tables. Cartesian graphs are also introduced as a way to show the variation of a quantity with respect to two parameters on the X and Y axes.
Basics of data_interpretation
This document provides information about data interpretation and different ways of presenting data. It discusses numerical data tables like time series tables, spatial tables, frequency distribution tables, and cumulative frequency tables. It then provides examples of data interpretation questions involving calculating percentages from tables showing production, sales, and capacity for three automobile companies from 1988-1998. Another example involves interpreting a table showing the number of members in different age and gender categories across six societies. Finally, it briefly discusses Cartesian graphs and types like single dependent variable graphs and graphs with more than one dependent variable.
STATISTICAL PROCEDURES (Discriptive Statistics).pptx
This document discusses statistical procedures and their applications. It defines key statistical terminology like population, sample, parameter, and variable. It describes the two main types of statistics - descriptive and inferential statistics. Descriptive statistics summarize and describe data through measures of central tendency (mean, median, mode), dispersion, frequency, and position. The mean is the average value, the median is the middle value, and the mode is the most frequent value in a data set. Descriptive statistics help understand the characteristics of a sample or small population.
2. week 2 data presentation and organization
Here are the answers to the questions:
A.
1. The variables in the graph are age (x-axis) and frequency (y-axis).
2. The variables are quantitative.
3. The variables are discrete.
4. No, a pie chart could not be used to display this data since it involves quantitative variables rather than categorical variables.
B.
1. A line graph would most appropriately represent the number of students enrolled at a local college for each year during the last 5 years. This involves two quantitative variables - years on the x-axis and enrollments on the y-axis.
2. A bar graph would most appropriately represent the frequency of each type of crime committed in
Statistica Sinica 16(2006), 847-860PSEUDO-R2IN LOGIS.docx
Statistica Sinica 16(2006), 847-860
PSEUDO-R
2
IN LOGISTIC REGRESSION MODEL
Bo Hu, Jun Shao and Mari Palta
University of Wisconsin-Madison
Abstract: Logistic regression with binary and multinomial outcomes is commonly
used, and researchers have long searched for an interpretable measure of the strength
of a particular logistic model. This article describes the large sample properties
of some pseudo-R2 statistics for assessing the predictive strength of the logistic
regression model. We present theoretical results regarding the convergence and
asymptotic normality of pseudo-R2s. Simulation results and an example are also
presented. The behavior of the pseudo-R2s is investigated numerically across a
range of conditions to aid in practical interpretation.
Key words and phrases: Entropy, logistic regression, pseudo-R2
1. Introduction
Logistic regression for binary and multinomial outcomes is commonly used
in health research. Researchers often desire a statistic ranging from zero to one
to summarize the overall strength of a given model, with zero indicating a model
with no predictive value and one indicating a perfect fit. The coefficient of deter-
mination R2 for the linear regression model serves as a standard for such measures
(Draper and Smith (1998)). Statisticians have searched for a corresponding in-
dicator for models with binary/multinomial outcome. Many different R2 statis-
tics have been proposed in the past three decades (see, e.g., McFadden (1973),
McKelvey and Zavoina (1975), Maddala (1983), Agresti (1986), Nagelkerke
(1991), Cox and Wermuch (1992), Ash and Shwartz (1999), Zheng and Agresti
(2000)). These statistics, which are usually identical to the standard R2 when
applied to a linear model, generally fall into categories of entropy-based and
variance-based (Mittlböck and Schemper (1996)). Entropy-based R2 statistics,
also called pseudo-R2s, have gained some popularity in the social sciences (Mad-
dala (1983), Laitila (1993) and Long (1997)). McKelvey and Zavoina (1975)
proposed a pseudo-R2 based on a latent model structure, where the binary/
multinomial outcome results from discretizing a continuous latent variable that
is related to the predictors through a linear model. Their pseudo-R2 is defined
as the proportion of the variance of the latent variable that is explained by the
848 BO HU, JUN SHAO AND MARI PALTA
covariate. McFadden (1973) suggested an alternative, known as “likelihood-
ratio index”, comparing a model without any predictor to a model including all
predictors. It is defined as one minus the ratio of the log likelihood with inter-
cepts only, and the log likelihood with all predictors. If the slope parameters
are all 0, McFadden’s R2 is 0, but it is never 1. Maddala (1983) developed
another pseudo-R2 that can be applied to any model estimated by the maximum
likelihood method. This popular and widely used measure is expressed as
R2M = 1 −
(
L(θ̃)
L(θ̂)
)
2
n
, (1)
.
Stations yourself somewhere (library, cafeteria, etc.) and observe.docx
Stations yourself somewhere (library, cafeteria, etc.) and observe the nonverbal communication that occurs.
What do people say with their bodies?
What messages are implicit in vocal expressions, clothes, make-up and so on?
Take notes on five of the most eloquent messages sent nonverbally.
*one page.
*Read the instructions then write about 5 difeerent people
.
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Sheet1Number of Visits Per DayNumber of Status Changes Per WeekAge.docx
Sheet1Number of Visits Per DayNumber of Status Changes Per WeekAge5138VariableMeanMedianModeRangeVarianceStandard Deviation15527Visits Per Day5121Status Changes Per Week25319Age50525631881024Data from:http://www.statcrunch.com/5.0/index.php?dataid=48537311028331910120114210481032112715118207190040003015526417311219414110320302051325324511851205621301201512053411551933190049543111182120422000520027101013531841219511820194121211811218124202019101018501002230224532050142337205120113331841514102541547319402010019004215320412800401166103145220122910524005032173119206310018212125719152202020002533310025512021332024002000211021002750201031911195718213810002221211532600361010245018511942202149311884185126013220102131371551500561502000285656185136001421471053022211012061352511800422083200212223113715520514520719106211581120332128241328233810540522111122113522632370035108540013761181120104194120004800.52351012128458221911390033321973025114820532022211272514471043405030191111004535281424602019201529105192002010140052342620718212630321120231800401910520151721942221071910719305041200058362143102251237120215119332632193832721356301810519421832351128531931193810221822310127425820234339204183218321900532238105411007519424318102362020171022040283850100292121286143250232319101025121823198204219442831293218203451432143117021181031815418530202521825104010263120101952243325102201511930220114131171051944240065231920220121443015121531851193024757144246203210213125621920275121104319121725104626191048102581181167441643400556320452051182024474181001841192312562481932339525214210494810255132310561312191155013650100181152101910552224191039210043302500560136814151263020107323262260415152124303193061004758108180039103900550050315910322602048404411354020http://www.statcrunch.com/5.0/index.php?dataid=485373
Sheet2
Sheet3
PSYC 354
Excel Homework 3
(70 pts possible)
The objective of your third Excel assignment is to learn to describe a data set using measures of central tendency and variability. First, be sure you view the presentation that covers computing central tendency and variability in Excel found in the Reading & Study folder in Module/Week 3. This presentation goes through the steps you will need to be familiar with in order to complete this assignment.
In Module/Week 3, the goal is to use Excel formulas to calculate specific measures of central tendency and variability of a given data set, using the steps you learned during the presentation. Open “Data Set 3,” found in the Assignment Instructions folder, under “Excel Homework 3,” then follow the steps below to complete Module/Week 3’s assignment.
1. Research Question: In Module/Week 3, the data comes from an internet survey that assessed the frequency of use of the social networking site Facebook ™. A psychologist interested in time spent visiting a social networking site collected data from 366 respondents concerning: 1.) number of visits to FB per day; 2.) number of times participants changed FB “status” per w.
Lesson 002
This document provides a summary of key concepts from Chapter 3 of a statistics textbook, including:
- How to calculate measures of central tendency like the mean, median, mode, and weighted mean
- The characteristics and properties of each measure
- How the positions of the mean, median and mode relate to the shape of the distribution
- How to calculate the mean, median and mode for grouped data
- What the geometric mean represents and how it is calculated
Biostatistics
This document provides an introduction to biostatistics and statistical concepts. It discusses descriptive statistics, which are used to describe data through measures like mean, median and mode. Inferential statistics are used to make inferences about populations based on sample data. Key terms are also defined, such as parameter (a population characteristic), statistic (a quantity calculated from a sample), population (the entire group being studied), and sample (a subset of a population). The document also covers topics like frequency distributions, graphical representation of data through graphs and diagrams, and how to construct tables and frequency distributions.
STAT200 Assignment #3 - Inferential Statistics Analysis an.docx
STAT200: Assignment #3 - Inferential Statistics Analysis and Writeup - Instructions
Page 1 of 5
STAT200 Introduction to Statistics
Assignment #3: Inferential Statistics Analysis and Writeup
Purpose:
The purpose of this assignment is to develop and carry out an inferential statistics analysis plan and
write up the findings. There are two main parts to this assignment:
● Part A: Inferential Statistics Data Plan and Analysis
● Part B: Write up of Results
Part A: Prepare Data Plan, Analyze Data, and Complete Part A of the Assignment #3 Template
➢ Task 1: Select Variables. Review the variables you used for assignments #1 and #2. Select your
qualitative socioeconomic variable as your grouping variable and the two expenditure variables
from the variables used in these previous assignments. Fill in Table 1: Variables Selected for
Analysis with name, description, and type of variable (i.e., qualitative or quantitative).
➢ Task 2: Select and Run a One Sample Confidence Interval Analysis. For one expenditure
variable, select and run the appropriate method for estimating a parameter, based on a statistic
(i.e., confidence interval method). Complete Table 2: Confidence Interval Information and
Results, which follows the format outlined by Kozak and the course’s problem-solving approach,
including:
○ Random variable stated in words
○ Confidence interval method, including rationale and assumptions
○ Method used for analyzing data (i.e., web applets, Excel, TI calculator, etc.).
○ Results obtained
○ Interpretation
➢ Task 3: Select Two Sample Hypothesis Test. Using the second expenditure variable (with the
socioeconomic variable as the grouping variable), select and run the appropriate method for
making decisions about two parameters relative to observed statistics (i.e., two sample
STAT200: Assignment #3 - Inferential Statistics Analysis and Writeup - Instructions
Page 2 of 5
hypothesis test method). Complete Table 3: Two Sample Hypothesis Test Analysis, which
follows the format outlined by Kozak and the course’s problem-solving approach, including:
○ Hypotheses (null and alternative).
○ Two sample hypothesis testing method, including rationale and assumptions
○ Method used for analyzing data (i.e., web applets, Excel, TI calculator, etc.).
○ Results obtained.
○ Interpretation (i.e., Reject the null hypothesis OR Fail to reject null hypothesis)
Step 2: Write Up Results and Complete Part B of the Assignment #3 Template
For this 1 to 2 page section, refer to the inferential statistics data plan and computations done for Part A
of this assignment. Address the following area:
➢ Introduction. Based on the scenario you submitted for the second assignment, provide a brief
description of scenario, including the variables that were used in this analysis. Include a
completed “Table 1: Variables Selected for Analysis to show the variables you selected for
analysis.
.
Quatitative Data Analysis
This document provides an overview of quantitative data analysis. It discusses data preparation, descriptive statistics such as measures of central tendency and dispersion, inferential statistics, and interpretation of results. The key steps in quantitative analysis are described as data preparation, describing the data through descriptive statistics, drawing inferences through inferential statistics, and interpreting the findings. Common statistical techniques like mean, median, mode, standard deviation, and correlation are also summarized.
Basics of data_interpretation
This document provides information about data interpretation and different ways to present data. It discusses numerical data tables including time series tables, spatial tables, frequency distribution tables, and cumulative frequency tables. Examples are given to show how to calculate capacity utilization, sales growth percentages, and solve other problems using the data in tables. Cartesian graphs are also introduced as a way to show the variation of a quantity with respect to two parameters on the X and Y axes.
Basics of data_interpretation
This document provides information about data interpretation and different ways of presenting data. It discusses numerical data tables like time series tables, spatial tables, frequency distribution tables, and cumulative frequency tables. It then provides examples of data interpretation questions involving calculating percentages from tables showing production, sales, and capacity for three automobile companies from 1988-1998. Another example involves interpreting a table showing the number of members in different age and gender categories across six societies. Finally, it briefly discusses Cartesian graphs and types like single dependent variable graphs and graphs with more than one dependent variable.
STATISTICAL PROCEDURES (Discriptive Statistics).pptx
This document discusses statistical procedures and their applications. It defines key statistical terminology like population, sample, parameter, and variable. It describes the two main types of statistics - descriptive and inferential statistics. Descriptive statistics summarize and describe data through measures of central tendency (mean, median, mode), dispersion, frequency, and position. The mean is the average value, the median is the middle value, and the mode is the most frequent value in a data set. Descriptive statistics help understand the characteristics of a sample or small population.
2. week 2 data presentation and organization
Here are the answers to the questions:
A.
1. The variables in the graph are age (x-axis) and frequency (y-axis).
2. The variables are quantitative.
3. The variables are discrete.
4. No, a pie chart could not be used to display this data since it involves quantitative variables rather than categorical variables.
B.
1. A line graph would most appropriately represent the number of students enrolled at a local college for each year during the last 5 years. This involves two quantitative variables - years on the x-axis and enrollments on the y-axis.
2. A bar graph would most appropriately represent the frequency of each type of crime committed in
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Statistica Sinica 16(2006), 847-860PSEUDO-R2IN LOGIS.docx
Statistica Sinica 16(2006), 847-860
PSEUDO-R
2
IN LOGISTIC REGRESSION MODEL
Bo Hu, Jun Shao and Mari Palta
University of Wisconsin-Madison
Abstract: Logistic regression with binary and multinomial outcomes is commonly
used, and researchers have long searched for an interpretable measure of the strength
of a particular logistic model. This article describes the large sample properties
of some pseudo-R2 statistics for assessing the predictive strength of the logistic
regression model. We present theoretical results regarding the convergence and
asymptotic normality of pseudo-R2s. Simulation results and an example are also
presented. The behavior of the pseudo-R2s is investigated numerically across a
range of conditions to aid in practical interpretation.
Key words and phrases: Entropy, logistic regression, pseudo-R2
1. Introduction
Logistic regression for binary and multinomial outcomes is commonly used
in health research. Researchers often desire a statistic ranging from zero to one
to summarize the overall strength of a given model, with zero indicating a model
with no predictive value and one indicating a perfect fit. The coefficient of deter-
mination R2 for the linear regression model serves as a standard for such measures
(Draper and Smith (1998)). Statisticians have searched for a corresponding in-
dicator for models with binary/multinomial outcome. Many different R2 statis-
tics have been proposed in the past three decades (see, e.g., McFadden (1973),
McKelvey and Zavoina (1975), Maddala (1983), Agresti (1986), Nagelkerke
(1991), Cox and Wermuch (1992), Ash and Shwartz (1999), Zheng and Agresti
(2000)). These statistics, which are usually identical to the standard R2 when
applied to a linear model, generally fall into categories of entropy-based and
variance-based (Mittlböck and Schemper (1996)). Entropy-based R2 statistics,
also called pseudo-R2s, have gained some popularity in the social sciences (Mad-
dala (1983), Laitila (1993) and Long (1997)). McKelvey and Zavoina (1975)
proposed a pseudo-R2 based on a latent model structure, where the binary/
multinomial outcome results from discretizing a continuous latent variable that
is related to the predictors through a linear model. Their pseudo-R2 is defined
as the proportion of the variance of the latent variable that is explained by the
848 BO HU, JUN SHAO AND MARI PALTA
covariate. McFadden (1973) suggested an alternative, known as “likelihood-
ratio index”, comparing a model without any predictor to a model including all
predictors. It is defined as one minus the ratio of the log likelihood with inter-
cepts only, and the log likelihood with all predictors. If the slope parameters
are all 0, McFadden’s R2 is 0, but it is never 1. Maddala (1983) developed
another pseudo-R2 that can be applied to any model estimated by the maximum
likelihood method. This popular and widely used measure is expressed as
R2M = 1 −
(
L(θ̃)
L(θ̂)
)
2
n
, (1)
.
Stations yourself somewhere (library, cafeteria, etc.) and observe.docx
Stations yourself somewhere (library, cafeteria, etc.) and observe the nonverbal communication that occurs.
What do people say with their bodies?
What messages are implicit in vocal expressions, clothes, make-up and so on?
Take notes on five of the most eloquent messages sent nonverbally.
*one page.
*Read the instructions then write about 5 difeerent people
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StatementState legislatures continue to advance policy proposals.docx
Statement
State legislatures continue to advance policy proposals to address cyber threats directed at governments and private businesses. As threats continue to evolve and expand and as the pace of new technologies accelerates, legislatures are making cybersecurity measures a higher priority.
Assignment
You are to author a 2-page (maximum) paper about the “failed” amendments proposed by the Kentucky legislature in 2019 with respect to Cyber Policy. APA format – 1 cover page, 2 content pages, and 1 reference page.
You are to answer two questions in your individual papers.
Brief background of the proposed amendment and “researched” speculation as to why it failed?
What would you propose for them to pass in 2020?
Remember to cite your sources appropriately and turn in original work!
Section 54
KY S 14
Status: Failed - Adjourned
Provides definitions relating to personal information, provides certain personal information that shall be protected from disclosure by a public agency or third-party contractor through redaction or other means, provides a list of covered persons, provides guidelines for contracts between a public agency and a third-party contractor.
.
StatementState legislatures continue to advance policy propo.docx
Statement
State legislatures continue to advance policy proposals to address cyber threats directed at governments and private businesses. As threats continue to evolve and expand and as the pace of new technologies accelerates, legislatures are making cybersecurity measures a higher priority.
Assignment
You are to author a 2-page (maximum) paper about the “failed” amendments proposed by the Kentucky legislature in 2019 with respect to Cyber Policy. APA format – 1 cover page, 2 content pages, and 1 reference page.
You are to answer two questions in your individual papers.
Brief background of the proposed amendment and “researched” speculation as to why it failed?
What would you propose for them to pass in 2020?
Remember to cite your sources appropriately and turn in original work!
KY S 14
Status: Failed - Adjourned
Provides definitions relating to personal information, provides certain personal information that shall be protected from disclosure by a public agency or third-party contractor through redaction or other means, provides a list of covered persons, provides guidelines for contracts between a public agency and a third-party contractor.
.
Statement of PurposeProvide a statement of your educational .docx
Statement of Purpose
Provide a statement of your educational background, experience, and preparation relevant to a graduate program in computer science, and specify your research and career goals.
The statement of purpose is a short essay introducing the applicant and his or her
interests, goals, and reasons for pursuing graduate study in history. Applicants may wish
to share a draft of their statement with the individuals writing their letters of
recommendation. While every statement, like every prospective student, will be different,
applicants should devote special attention to the following items:
• Academic/Professional Background: Please give your academic credentials, with
degrees, dates, and relevant employment experience. You do not need to list every
job you have had, only those that bear directly on your desire to enter graduate
school.
• Motivations and Aims: Explain what motivates you to do graduate work in history
and what your goals are, both within the graduate program and after the
completion of your degree.
• Existing Expertise and Accomplishments in History: Discuss any areas of
expertise you may already have in your proposed area of interest. If you have
experience doing research, please describe the project and your work on it. If you
have any special talents or skills, such as a foreign language, please describe
them.
• Proposed Course of Study: Please identify planned major field and minor fields of
study.
• Other Relevant Experiences or Personal Qualities: Discuss any experiences or
personal attributes that may illuminate your commitment to the study of history
and to the successful completion of the graduate program.
Format: Your statement of purpose should be limited to no more than 750 words
(between 2 and 3 pages).
.
States and the federal government should not use private prisons for.docx
States and the federal government should not use private prisons for various reasons. First, most of the private prisons are for-profit facilities. Therefore, they cut on expenses such as lacking enough staffing and resources, which is likely to affect inmates' safety and quality of life. Further, while pro-private prisons note that private prisons save taxpayers' money, studies indicate that they do not reduce costs. For instance, the day to day cost of housing an inmate in 2010 was $53.02 for private prisons compared to $48.42 for a medium-security public prison (Pedowitz, 2012). Also, prisoners do not receive similar kinds of treatment in private facilities. While they may be suitable for the local economy, such as offering job opportunities, lowering costs by private facilities leaves inmates sick and not well cared for (NPR Staff, 2011).
.
StatementState legislatures continue to advance policy proposa.docx
The document discusses a 2-page paper assignment on failed cybersecurity amendments proposed by the Kentucky legislature in 2019. Students are asked to analyze why one amendment failed and propose a new amendment for 2020. The failed amendment, KY S 14, aimed to protect personal information from disclosure by public agencies or third-party contractors.
Statement of Interest (This is used to apply for Graduate Schoo.docx
Statement of Interest: (This is used to apply for Graduate School, digital media program)
Length: 2 pages. (500-750 words)
Area of interest in digital media.
-computational arts.
I did a mix media group exhibition in Feb. 2018 called What Makes You You. Half of my show is a sculpture-based installation. The other half is an interactive digital programed art(using Processing software). The visual of human evolution ties these two park together. See details at https://dongpu.weebly.com/what-makes-you-you.html
-short videos (documentary production).
I love shooting short videos. I formed a Youtube team called 2037 Club last year. https://www.youtube.com/channel/UCmtUQfDMvL9iE8IOy9oshSA
The latest documentary I did is called Liang(Grain). Video Statement：This documentary discovers the Chinese planned economy history period, which starts at the 1950s. People were given a certain amount of coupons to buy food and daily needs because of the limitation of products. Since this is a historical theme, reference images are included to support the concept of buying food today and before 1990. Other than that, the visuals are mainly about common people’s daily routine nowadays. Along with the visual, the most artistic part in this video is Shanghainese dialogue, which explained food coupons in the way of storytelling. “I accidentally found many food coupons in my grandparents’ house this summer, so I went to ask them about the experiences they had with these coupons. My curiosity leads me to the theme.” said by the producer.
This particular video also has a different meaning to me. My Grandmother passed away one week before the video published at the film festival (at Scottsdale Museum of Commemoratory Art). This piece becomes memorable to me, sadly, my grandmother never had a chance to see the whole piece.
https://www.youtube.com/watch?v=fD0Y-BXDfnY
-3D animation for games
I learned Maya in an animation course. Like editing videos, I soon full in love with 3D modeling.
https://www.youtube.com/watch?v=nGIRxaUdYiY
Business idea, if an applicant has one. It is fine if an applicant is unsure when applying to the program. It is also fine if an applicant is interested in the artistic aspect of digital media and not the entrepreneurial aspect.
I would like to complete a mobile game project in my Graduate studies period and start a game company after graduation. Meanwhile, still active in the art field being an intermedia artist.
Goals or expectations upon completion of the digital media program.
-I want to learn more about computer technologies to create artistic works. Focusing on the field of game development.
-Do more social, get to know people in my field
-Get professional advices of my projects
Here is my cover letter, you can utilize this for the statement of interest.
As a creative and passionate professional with a rich history of developing creative materials, I am eager to submit my resume for consideration for the (Position Title) position .
StatementState legislatures continue to advance policy prop.docx
Statement
State legislatures continue to advance policy proposals to address cyber threats directed at governments and private businesses. As threats continue to evolve and expand and as the pace of new technologies accelerates, legislatures are making cybersecurity measures a higher priority.
Assignment
You are page amendments to author a 2-page (maximum) paper about the “failed” amendments proposed by the Kentucky legislature in 2019 with respect to Cyber Policy. APA format – 1 cover page, 2 content pages, and 1 reference pageamendments proposed.
You are to answer two questions in your individual papers.
Brief background of the proposed amendment and “researched” speculation as to why it failed?
What would you propose for them to pass in 2020?
.
Statement of cash flows (indirect method) Cash flows from ope.docx
Statement of cash flows (indirect method)
Cash flows from operating activities
Net income
72,600
adjustments to net income
depreciation
4,000
Gan on sale of investments
-7,000
Increase in AR
-36,000
Decrease in inventory
40,000
Increased in Accounts payable
13,000
Decrease in Accrued liabilities
-3,100
net cash provided by operating activities
83,500
Cash flows from investing activities
Purchase of Plant assets
-16,000
Sale of long-term investments
20,000
net cash provided by investing activities
4,000
Cash flows from financing activities
retiement of bonds
-31,000
payment of dividend
-32,500
sale of common stock
6,000
net cash provided by financing activities
-57,500
net increase in cash
30,000
Cash balance, beginning
230,000
cash balance, ending
260,000
Statement of Cash flows (direct method)
Cash flows from operating activities
cash received from customers
714,000
(sales - increase in AR)
cash paid for merchandise
477,000
(cogs - decrease in invnetory - increase in AP)
cash paid for other operating expenes
105,100
(selling & admin exp + decrease in accrued liab - depreciation)
cash paid for income taxes
48,400
net cash provided b oeprating activities
83,500
Cash flows from investing activities
Purchase of Plant assets
-16,000
Sale of long-term investments
20,000
net cash provided by investing activities
4,000
Cash flows from financing activities
retiement of bonds
-31,000
payment of dividend
-32,500
sale of common stock
6,000
net cash provided by financing activities
-57,500
net increase in cash
30,000
Cash balance, beginning
230,000
cash balance, ending
260,000
.
Stateline Shipping and Transport CompanyRachel Sundusky is the m.docx
Stateline Shipping and Transport Company
Rachel Sundusky is the manager of the South-Atlantic office of the Stateline Shipping and Transport Company. She is in the process of negotiating a new shipping contract with Polychem, a company that manufactures chemicals for industrial use. Polychem want Stateline to pick up and transport waste products from its six plants to three waste disposal sites. Rachel is very concerned about this proposed arrangement. The chemical wastes that will be hauled can be hazardous to humans and the environment if they leak. In addition, a number of towns and communities in the region where the plants are located prohibit hazardous materials from being shipped through their municipal limits. Thus, not only will the shipments have to be handled carefully and transported at reduced speeds, they will also have to traverse circuitous routes in many cases. Rachel has estimated the cost of shipping a barrel of waste from each of the six plants to each of the three waste disposal sites as shown in the following table:
Waste Disposal Site
Plant
Whitewater
Los Canos
Duras
Kingsport
$12
$15
$17
Danville
14
9
10
Macon
13
20
11
Selma
17
16
19
Columbus
7
14
12
Allentown
22
16
18
The plants generate the following amounts of waste products each week:
Plant
Waste per Week (bbl)
Kingsport
35
Danville
26
Macon
42
Selma
53
Columbus
29
Allentown
38
The three waste disposal sites at Whitewater, Los Canos, and Duras can accommodate a maximum of 65, 80, and 105 barrels per week respectively. In addition to shipping directly from each of the six plants to one of the three waste disposal sites, Rachel is also considering using each of the plants and waste disposal sites as intermediate shipping points. Trucks would be able to drop a load at a plant or disposal site to be picked up and carried on to the final destination by another truck, and vice versa. Stateline would not incur any handling costs because Polychem has agreed to take care of all local handling of the waste materials at the plants and the waste disposal sites. In other words, the only cost Stateline incurs is the actual transportation cost. So Rachel wants to be able to consider the possibility that it may be cheaper to drop and pick up loads at intermediate points rather than ship them directly. Rachel estimates the shipping costs per barrel between each of the six plants to be as follows:
Plant
Plant
Kingsport
Danville
Macon
Selma
Columbus
Allentown
Kingsport
$ __
$6
$4
$9
$7
$8
Danville
6
__
11
10
12
7
Macon
5
11
__
3
7
15
Selma
9
10
3
__
3
16
Columbus
7
12
7
3
__
14
Allentown
8
7
15
16
14
__
The e.
State Two ways in which Neanderthals and Cro-Magnons differed. .docx
State Two ways in which Neanderthals and Cro-Magnons differed.
List an important achievement for each of these scientist. Aristarchus, Euclid, Archimedes, and Herophilus
"Civilizations" is defined as the stage of development in which people have developed :
1. large, permanet communites.
2. a system of writing
3. divirsion
4. trade
5. a srtong central goverment
.
STAT 3300 Homework #6Due Thursday, 03282019Note Answe.docx
This document outlines a homework assignment for a statistics course. It provides details on a multiple regression analysis examining the relationship between average student debt and various college metrics like admission rates, graduation rates, and in-state costs. The assignment asks students to conduct the multiple regression, analyze residuals, test hypotheses, and determine which variables are significant predictors of debt. It also provides learning objectives for a chapter on juvenile justice treatment and prevention programs.
State Standard by Content AreaLiteracy State Standard to Integra.docx
State Standard by Content Area
Literacy State Standard to Integrate into Another Content Area
Use a different literacy standard for each content standard.
Standards-based Learning Objective
Aligned to content standards
Instructional Strategy to Integrate Literacy
Resources
Provide links to websites, PDFs, and any other documents used or referenced for strategy
Rationale
How the strategy will promote balanced literacy curriculum
State Content Standard 1:
State Content Standard 2:
State Content Standard 3:
.
STAT200 Assignment #2 - Descriptive Statistics Analysis and.docx
STAT200: Assignment #2 - Descriptive Statistics Analysis and Writeup - Instructions
Page 1 of 3
STAT200 Introduction to Statistics
Assignment #2: Descriptive Statistics Analysis and Writeup
Assignment #2: Descriptive Statistics Analysis and Writeup
In the first assignment (Assignment #1: Descriptive Statistics Analysis Data Plan), you developed a
scenario about annual household expenditures and a plan for analyzing the data using descriptive
statistic methods. The purpose of this assignment is to carry out the descriptive statistics analysis plan
and write up the results. The expected outcome of this assignment is a two to three page write-up of
the findings from your analysis as well as a recommendation.
Assignment Steps:
Step #1: Review Feedback from Your Instructor
Before performing any analysis, please make sure to review your instructor’s feedback on Assignment
#1: Descriptive Statistics Data Analysis Plan. Based on the feedback, modify variables, tables, and
selected statistics, graphs, and tables, if needed.
Step #2: Perform Descriptive Statistic Analysis
Task 1: Look at the dataset.
• (Re)Familiarize yourself with the variables. Review Table 1: Variables Selected for the
Analysis you generated for the first assignment as well as your instructor’s feedback. In
addition, look at the data dictionary contained in the data set for information about the
variables.
• Select the variables you need for the analysis.
Task 2: Complete your data analysis, as outlined in your first assignment, with any needed
modifications, based on your instructor’s feedback.
• Calculate Measures of Central Tendency and Variability. Use the information from
Assignment #1 - Table 2. Numerical Summaries of the Selected Variables. Here again,
be sure to see your instructor’s feedback and incorporate into the analysis.
• Prepare Graphs and/or Tables. Use the information from Assignment #1 - Table 3.
Type of Graphs and/or Tables for Selected Variables. Here again, be sure to see your
instructor’s feedback and incorporate into the analysis.
STAT200: Assignment #2 - Descriptive Statistics Analysis and Writeup - Instructions
Page 2 of 3
Step #3: Write-up findings using the Provided Template
For this part of the assignment, write a short 2-3 page write-up of the process you followed and the
findings from your analysis. You will describe, in words, the statistical analysis used and present the
results in both statistical/text and graphic formats.
Here are the main sections for this assignment:
✓ Identifying Information. Fill in information on name, class, instructor, and date.
✓ Introduction. For this section, use the same scenario you submitted for the first assignment and
modified using your instructor’s feedback, if needed. Include Table 1 (Table 1: Variables
Selected for the Analysis) you used in Assignment #1 to show the variables you selected for the
analysis.
✓ Data .
State legislatures continue to advance policy proposals to address c.docx
The document discusses a 2-page paper assignment on failed cybersecurity policy amendments proposed by the Kentucky legislature in 2019. Students are asked to answer two questions: 1) provide a brief background on a proposed amendment that failed and speculate on why it failed, and 2) propose an amendment for the legislature to pass in 2020. The assignment requires citing sources and original work, and is due by the specified date. It also provides background on one failed proposed amendment related to protecting personal information.
State FLORIDAInstructionsThis written assignment requ.docx
State: FLORIDA
Instructions
This written assignment requires the student to investigate his/her local, state and federal legislators and explore their assigned committees and legislative commitments. The student is expected to investigate current and actual legislative initiatives that have either passed or pending approval by the house, senate or Governor’s office. The student will draft a letter to a specific legislator and offer support or constructive argument against pending policy or legislation. The letter must be supported with a minimum of 3 evidence based primary citations. (See Rubric)
Submission Details:
Support your responses with examples.
Cite any sources in APA format.
Submit your document to the
Submissions Area
by
the due date assigned.
.
State of the Science Quality ImprovementNameInst.docx
State of the Science Quality ImprovementNameInstitutionsDate
Abstract
The condition of chronic heart failure sometimes is referred to as congestive heart failure (CHF), which is recognized as an acute life-threatening disease that majorly affects millions of American citizens annually. The condition of the chronic heart failure results when the heart is incapable of sufficient pump the blood throughout the body tissues due to the weak heart muscles (January et al., 2019). Certain conditions, such as narrowed arteries in the heart (CAD) or high blood pressure, gradually leave the heart too weak or stiff to fill and pump efficiently. Moreover, there are some of the several conditions such as coronary artery diseases and hypertension that leads to acute and chronic heart failure in the body system. More importantly, to avoid the possibility of this dangerous condition as well as the ever-increasing of the re-admitted hospital continue, collectively, the patient must be able to control the earlier stated conditions along with diabetes as well as obesity at home-based care and with their primary healthcare providers as well. According to Santesmases-Masana et al. (2019), "Primary health care planned care has been shown to reduce heart failure re-hospitalizations and maintain the patient quality of life." With this known knowledge, it is important to continue care at home and with their primary care provider to monitor and detect worsening of their condition sooner rather than later with evidence-based treatment practices. There are many evidence-based treatments for chronic heart failure that includes monitoring of vital signs, weight, and diet along with medications. In this paper, chronic heart failure, problem discussion, PICO question, and theoretical framework will be presented.
Problem Discussion
Chronic heart failure is a chief public health care concern linked with the high degree of mortality and morbidity in the U.S. Heart failure usually results in adverse outcomes, and the most costly is the issues of hospital readmissions. Currently, the heart failure management clinical procedures and pieces of evidence emphasizes the significance and the function of the care interventions a mid preventing the heart failure readmissions in the hospital set up. The current literature review is meant to evaluate and assess the effectiveness of transitional care interventions that intend to minimize hospital readmissions. Increase hospital readmission and worsening chronic heart failure complications are due to lack of following of a primary care provider and home monitoring of vital signs, weight, diet, energy level, and breathing patterns by the patient. There are many evidence-based practices and comprehensive guidelines for chronic heart failure treatment with side effects of some medications about individual races. For instance, losartan has little to adverse impact on blacks. Furthermore, according to Hadidi et al. (2018), "It has been.
State Data_1986-2015YearGross state product per capitaEducation sp.docx
The document provides data on various metrics for a U.S. state from 1986 to 2016 including gross state product per capita, education spending per student, unemployment rates, and high school graduation rates. It shows trends over time, with generally increasing economic output and education spending, and decreasing unemployment and increasing graduation rates. The data could help inform policymaking and planning.
State and major urban area fusion centers serve as focal points wi.docx
State and major urban area fusion centers serve as focal points within the state and local environment for the receipt, analysis, gathering, and sharing of threat-related information between the federal government and state, local, tribal, territorial (SLTT), and private sector partners.
There are issues and concerns related to intelligence collection methods at some of the country's local law enforcement agencies, joint terrorism task groups, and fusion centers. The first issue relates to constitutional limitations. Constitutional limitations restrict the government’s ability to access private information. The Fourth Amendment to the U.S. Constitution is particularly relevant. To the extent that government activity burdens individuals’ freedom of speech and related rights, the First Amendment may also play a role. Another issue is related to the process of collecting and sharing the information, which in many cases is not standardized, creating potential holes in the way officials exchange information on terror threats.
1. Briefly describe the six-step intelligence cycle.
2. What are some potential problems with collecting intelligence within the United States?
3. Give some examples of fusion centers and how these centers fuse intelligence at the local, state, and federal levels.
1. What is DHS’s Intelligence role in Homeland Security?
2. What are the roles of the National Counterterrorism Center (NCTC) and FBI for national intelligence? How do these roles benefit DHS?
.
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STAT200 Assignment #2 - Descriptive Statistics Analysis Writeup -.docx
- 1. STAT200: Assignment #2 - Descriptive Statistics Analysis Writeup - Template Page 3 of 3 University of Maryland University College STAT200 - Assignment #2: Descriptive Statistics Analysis and Writeup Identifying Information Student (Full Name): Class: Instructor: Date: Introduction: Use the same scenario you submitted for the first assignment with modifications using your instructor’s feedback, if needed. Include Table 1: Variables Selected for the Analysis you used in Assignment #1 to show the variables you selected for analysis. Table 1. Variables Selected for the Analysis Variable Name in data set Description Type of Variable (Qualitative or Quantitative) Variable 1: “Income” Annual household income in USD. Quantitative Variable 2: Variable 3:
- 2. Variable 4: Variable 5: Data Set Description and Method Used for Analysis: Results: Variable 1: Income Numerical Summary. Table 2. Descriptive Analysis for Variable 1 Variable n Measure(s) of Central Tendency Measure(s) of Dispersion Variable: Income Median= SD = Graph and/or Table: Histogram of Income (Place Histogram here) Description of Findings. Variable 2: (Fill in name of variable) Numerical Summary. Table 3. Descriptive Analysis for Variable 2 Variable
- 3. n Measure(s) of Central Tendency Measure(s) of Dispersion Variable: Graph and/or Table. (Place Graph or Table Here) Description of Findings. Variable 3: (Fill in name of variable) Numerical Summary. Table 4. Descriptive Analysis for Variable 3 Variable n Measure(s) of Central Tendency Measure(s) of Dispersion Variable: Graph and/or Table. (Place Graph or Table Here) Description of Findings. Variable 4: (Fill in name of variable) Numerical Summary.
- 4. Table 5. Descriptive Analysis for Variable 4 Variable N Mean/Median St. Dev. Variable 4: Graph and/or Table. (Place Graph or Table Here) Description of Findings. Variable 5: (Fill in name of variable) Numerical Summary. Table 6. Descriptive Analysis for Variable 5 Variable n Measure(s) of Central Tendency Measure(s) of Dispersion Variable: Graph and/or Table. (Place Graph or Table Here) Description of Findings. Discussion and Conclusion. Briefly discuss each variable in the same sequence as presented
- 5. in the results. What has the highest expenditure? What variable has the lowest expenditure? If you were to recommend a place to save money, which expenditure would it be and why? Note: The section should be no more than 2 paragraphs. STAT200 Introduction to Statistics Dataset for Written Assignments Description of Dataset: The data is a random sample from the US Department of Labor’s 2016 Consumer Expenditure Surveys (CE) and provides information about the composition of households and their annual expenditures (https://www.bls.gov/cex/). It contains information from 30 households, where a survey responder provided the requested information; it is all self-reported information. This dataset contains four socioeconomic variables (whose names start with SE) and four expenditure variables (whose names start with USD). Description of Variables/Data Dictionary: The following table is a data dictionary that describes the variables and their locations in this dataset (Note: Dataset is on second page of this document): Variable Name Location in Dataset Variable Description Coding UniqueID# First Column Unique number used to identify each survey responder Each responder has a unique number from 1-30 SE-MaritalStatus Second Column Marital Status of Head of Household Not Married/Married
- 6. SE-Income Third Column Annual Household Income Amount in US Dollars SE-AgeHeadHousehold Fourth Column Age of the Head of Household Age in Years SE-FamilySize Fifth Column Total Number of People in Family (Both Adults and Children) Number of People in Family USD-Annual Expenditures Sixth Column Total Amount of Annual Expenditures Amount in US Dollars USD-Food Seventh Column Total Amount of Annual Expenditure on Food Amount in US Dollars USD-Entertainment Eighth Column Total Amount of Annual Expenditure on Entertainment Amount in US Dollars USD-Education Ninth Column Total Amount of Annual Expenditure on Education Amount in US Dollars How to read the data set: Each row contains information from one household. For instance, the first row of the dataset starting on the next page shows us that: the head of household is not married and is 40 years old, has an annual household income of $98,717, a family size of 3, annual expenditures of $56,393, and spends $7,036 on food, $106 on entertainment, and $213 on education.
- 8. 56097 6822 88 252 4 Not Married 96664 53 3 55558 7051 83 295 5 Not Married 96886 44 2 55321 6982 79 312 6 Not Married 96522 43 4 56152 6991 101 237 7 Not Married 97912 49 1
- 9. 55704 6937 97 277 8 Not Married 96727 39 2 56440 7051 93 222 9 Not Married 96928 43 3 55932 6953 105 273 10 Not Married 95744 52 4 55963 7040 105 340 11 Not Married 97681 53 4
- 10. 56124 7097 108 263 12 Not Married 95432 51 1 55120 7089 84 274 13 Not Married 94929 59 2 55247 6948 97 236 14 Not Married 96621 54 2 55746 7000 106 322 15 Not Married 95366 48 2
- 14. 73114 8922 131 463 28 Married 99610 36 2 73550 9513 158 37 29 Married 114505 36 5 78325 11375 60 482 30 Married 106977 56 3 79358 10611 109 311 STAT200: Assignment #1 - Descriptive Statistics Analysis Plan - Template Page 1 of 3
- 15. University of Maryland University College STAT200 - Assignment #1: Descriptive Statistics Data Analysis Plan Identifying Information Student (Full Name): Class: Instructor: Date: Scenario: Please write a few lines describing your scenario and the four variables (in addition to income) you have selected. Use Table 1 to report the variables selected for this assignment. Note: The information for the required variable, “Income,” has already been completed and can be used as a guide for completing information on the remaining variables. Table 1. Variables Selected for the Analysis Variable Name in the Data Set Description (See the data dictionary for describing the variables.) Type of Variable (Qualitative or Quantitative) Variable 1: “Income” Annual household income in USD. Quantitative Variable 2: Variable 3:
- 16. Variable 4: Variable 5: Reason(s) for Selecting the Variables and Expected Outcome(s): Variable 1: “Income” - Variable 2: “ “ - Variable 3: “ “ - Variable 4: “ “ - Variable 5: “ “ - Data Set Description: Proposed Data Analysis: Measures of Central Tendency and Dispersion Complete Table 2. Numerical Summaries of the Selected Variables and briefly explain why you choose those measurements. Note: The information for the required variable, “Income,” has already been completed and can be used as a guide for completing information on the remaining variables. Table 2. Numerical Summaries of the Selected Variables Variable Name Measures of Central Tendency and Dispersion Rationale for Why Appropriate Variable 1: “Income” Number of ObservationsMedianSample Standard Deviation I am using median for two reasons:If there are any outliers or the data is not normally distributed, the median is the best measure of central tendency.The variable is quantitative.
- 17. I am using sample standard deviation for three reasons:The data is a sample from a larger data set.It is the most commonly used measure of dispersion.The variable is quantitative. Variable 2: Variable 3: Variable 4: Variable 5: Graphs and/or Tables Complete Table 3. Type of Graphs and/or Table for Selected Variables and briefly explain why you choose those graphs and/or tables. Note: The information for the required variable, “Income,” has already been completed and can be used as a guide for completing information on the remaining variables. Table 3. Type of Graphs and/or Tables for Selected Variables Variable Name Graph and/or Table Rationale for why Appropriate? Variable 1: “Income” Graph: I will use the histogram to show the normal distribution of data. Histogram is one of the best plot to show the normal
- 18. distribution of quantitative level data . Variable 2: Variable 3: Variable 4: Variable 5: