Bar graphs
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Bar graphs and pie charts are used to visualize categorical data. Bar graphs show counts or percentages of observations in different categories using rectangular bars of varying heights. Pie charts show the proportion of a whole taken up by different categories using slices of a circle. This document provides examples and steps for creating bar graphs and discusses when pie charts can and cannot be used based on whether the data sums to 100%.
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![Bar Graphs ,[object Object],[object Object],[object Object],[object Object],[object Object],Mrs. Kristen Ulshafer Mathematics Teacher 6/16/2011 Marital Status Count (millions) Percent Never Married 43.9 22.9 Married 116.7 60.9 Widowed 13.4 7.0 Divorced 17.6 9.2 191.6 100](https://image.slidesharecdn.com/bargraphs-110616150954-phpapp02/85/Bar-graphs-1-320.jpg)
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a. The time required to produce each tire on an assembly line – ratio since it is numeric with a valid 0 point meaning “lack of”
b. The number of quarts of milk a family drinks in a month - ratio since it is numeric with a valid 0 point meaning “lack of”
c. The ranking of four machines in your plant after they have been designated as excellent, good, satisfactory, and poor – ordinal since it is ranking data only
d. The telephone area code of clients in the United States – nominal since it is a label
e. The age of each of your employees - ratio since it is numeric with a valid 0 point meaning “lack of”
f. The dollar sales at the local pizza house each month - ratio since it is numeric with a valid 0 point meaning “lack of”
g. An employee’s identification number – nominal since it is a label
h. The response time of an emergency unit - ratio since it is numeric with a valid 0 point meaning “lack of”
2) True or False: The highest level of data measurement is the ratio-level measurement.
True (you can do the most powerful analysis with this kind of data)
3) True or False: Interval- and ratio-level data are also referred to as categorical data.
False (Interval and ratio level data are numeric and therefore quantitative, NOT qualitative….Nominal is qualitative)
4) A small portion or a subset of the population on which data is collected for conducting statistical analysis is called __________.
A sample! A population is the total group, a census IS the population, and a data set can be either a sample or a population.
5) One of the advantages for taking a sample instead of conducting a census is this:
a sample is more accurate than census
a sample is difficult to take
a sample cannot be trusted
a sample can save money when data collection process is destructive
6) Selection of the winning numbers is a lottery is an example of __________.
convenience sampling
random sampling
nonrandom sampling
regulatory sampling
7) A type of random sampling in which the population is divided into non-overlapping subpopulations is called __________.
stratified random sampling
cluster sampling
systematic random sampling
regulatory sampling
8) A ...
Chapter3
This document provides examples and explanations of various graphical methods for describing data, including frequency distributions, bar charts, pie charts, stem-and-leaf diagrams, histograms, and cumulative relative frequency plots. It demonstrates how to construct these graphs using sample data on student weights, grades, ages, and other examples. The goal is to help readers understand different ways to visually represent data distributions and patterns.
Math Module Sample
Here are the steps to make a frequency table for the ages at which some Filipinos drop out of school:
1. List the raw data:
18, 21, 17, 15, 34, 42, 32, 24, 28, 27, 21, 18, 17, 32, 34, 36, 37, 23, 25, 45, 22, 19, 20, 21, 19, 19, 20, 29, 30, 31, 17, 35, 25, 25, 8, 14, 7, 9, 8, 7, 17, 12, 9, 12, 12, 11, 16, 15, 14, 13, 9, 10, 10, 15, 17, 16, 16, 12,
Statistics three
This document provides an overview of different types of charts for visualizing data, including pie charts, bar charts, histograms, step charts, and ogives. It discusses when each chart is most appropriate based on the type of data (nominal, ordinal, discrete metric, continuous metric). For each chart type, it provides examples and discusses how to properly construct and interpret the charts. It also covers concepts like bimodal distributions and the normal distribution as they relate to interpreting chart shapes.
Chapter03
The document discusses various graphical methods for describing data, including bar charts, pie charts, stem-and-leaf diagrams, histograms, and cumulative relative frequency plots. It provides examples of each using sample student data on vision correction methods, weights, ages, and GPAs to illustrate how to construct and interpret the different graph types.
Chapter03
The document discusses various graphical methods for describing data, including bar charts, pie charts, stem-and-leaf diagrams, histograms, and cumulative relative frequency plots. It provides examples of each using sample student data on vision correction, weights, ages, and GPAs to illustrate how to construct and interpret the different graph types.
Business Statistics Chapter 2
This document summarizes the key topics and concepts covered in Chapter 2 of the 9th edition of the business statistics textbook "Presenting Data in Tables and Charts". The chapter discusses guidelines for analyzing data and organizing both numerical and categorical data. It then covers various methods for tabulating and graphing univariate and bivariate data, including tables, histograms, frequency distributions, scatter plots, bar charts, pie charts, and contingency tables.
TSTD 6251 Fall 2014SPSS Exercise and Assignment 120 PointsI.docx
TSTD 6251 Fall 2014
SPSS Exercise and Assignment 1
20 Points
In this class, we are going to study descriptive summary statistics and learn how to construct box plot. We are still working with univariate variable for this exercise.
Practice Example:
Admission receipts (in million of dollars) for a recent season are given below for the
n =
30 major league baseball teams:
19.4 26.6 22.9 44.5 24.4 19.0 27.5 19.9 22.8 19.0 16.9 15.2 25.7 19.0 15.5 17.1 15.6 10.6 16.2 15.6 15.4 18.2 15.5 14.2 9.5 9.9
10.7 11.9 26.7 17.5
Require:
a. Compute the mean, variance and standard deviation.
b. Find the sample median, first quartile, and third quartile.
c. Construct a boxplot and interpret the distribution of the data.
d. Discuss the distribution of this set of data by examining kurtosis and skewness
statistics, such as if the distribution is skewed to one side of the distribution, and if the
distribution shows a peaked/skinny curve or a spread out/flat curve.
SPSS Procedures for Computing Summary Statistics
:
Enter the 30 data values in the first column of SPSS
Data View
Tab
Variable View
and name this variable
receipts
Adjust
Decimals
to 3 decimal points
Type
Admission Receipts
($ mn)
in the
Label
column for output viewer
Return to
Data View
and click
A
nalyze
on the menu bar
Click the second menu
D
e
scriptive Statistics
Click
F
requencies …
Move
Admission Receipts
to the
Variable(s)
list by clicking the arrow button
Click
S
tatistics …
button at the top of the dialog box
Now, you can select the descriptive statistics according to what the question requires. For this practice question, it requires central tendency, dispersion, percentile and distribution statistics, so we click all the boxes
except for
P
ercentile(s): and Va
l
ues are group midpoints
.
Click
Continue
to return to the
Frequencies
dialog box
Click
OK
to generate descriptive statistic output which is pasted below:
The first table provides summary statistics and the second table lists frequencies, relative frequencies and cumulative frequencies. The statistics required for solving this problem are highlighted in red.
Statistics
Admission Receipts
N
Valid
30
Missing
0
Mean
18.76333
Std. Error of Mean
1.278590
Median
17.30000
Mode
19.000
Std. Deviation
7.003127
Variance
49.043782
Skewness
1.734
Std. Error of Skewness
.427
Kurtosis
5.160
Std. Error of Kurtosis
.833
Range
35.000
Minimum
9.500
Maximum
44.500
Sum
562.900
Percentiles
10
10.61000
20
14.40000
25
15.35000
30
15.50000
40
15.84000
50
17.30000
60
19.00000
70
19.75000
75
22.82500
80
24.10000
90
26.69000
Admission Receipts
Frequency
Percent
Valid Percent
Cumulative Percent
Valid
9.500
1
3.3
3.3
3.3
9.900
1
3.3
3.3
6.7
10.600
1
3.3
3.3
10.0
10.700
1
3.3
3.3
13.3
11.900
1
3.3
3.3
16.7
14.200
1
3.3
3.3
20.0
15.2.
TitleABC123 Version X1Practice Set 1QNT275 Version.docx
Title
ABC/123 Version X
1
Practice Set 1
QNT/275 Version 6
1
University of Phoenix Material
Practice Set 1
Practice Set 1
1. The following table lists the number of deaths by cause as reported by the Centers for Disease Control and Prevention on February 6, 2015:
Cause of Death
Number of Deaths
Heart disease
611,105
Cancer
584,881
Accidents
130,557
Stroke
128,978
Alzheimer's disease
84,767
Diabetes
75,578
Influenza and Pneumonia
56,979
Suicide
41,149
a) What is the variable for this data set (use words)?
b) How many observations are in this data set (numeral)?
c) How many elements does this data set contain (numeral)?
2. Indicate which of the following variables are quantitative and which are qualitative.
Note: Spell quantitative and qualitative in lower case letters.
a) The amount of time a student spent studying for an exam
b) The amount of rain last year in 30 cities
c) The arrival status of an airline flight (early, on time, late, canceled) at an airport
d) A person's blood type
e) The amount of gasoline put into a car at a gas station
3. A local gas station collected data from the day's receipts, recording the gallons of gasoline each customer purchased. The following table lists the frequency distribution of the gallons of gas purchased by all customers on this one day at this gas station.
Gallons of Gas
Number of Customers
4 to less than 8
78
8 to less than 12
49
12 to less than 16
81
16 to less than 20
117
20 to less than 24
13
a) How many customers were served on this day at this gas station?
b) Find the class midpoints. Do all of the classes have the same width? If so, what is this width? If not, what are the different class widths?
c) What percentage of the customers purchased between 4 and 12 gallons? (do not include % sign. Round numerical value to one decimal place)
4. The following data give the one-way commuting times (in minutes) from home to work for a random sample of 50 workers.
23
17
34
26
18
33
46
42
12
37
44
15
22
19
28
32
18
39
40
48
16
11
9
24
18
26
31
7
30
15
18
22
29
32
30
21
19
14
26
37
25
36
23
39
42
46
29
17
24
31
a. What is the frequency for each class 0–9, 10–19, 20–29, 30–39, and 40–49.
b. Calculate the relative frequency and percentage for each class.
c. What percentage of the workers in this sample commute for 30 minutes or more?
Note: Round relative frequency to two decimal places. Complete the table by calculating the frequency, relative frequency, and percentage.
Commuting Times
Frequency
(part a)
Relative Frequency
(part c)
Percentage (%)
(part d)
0-9
?
0.??
?
10-19
?
0.??
?
20-29
?
0.??
?
30-39
?
0.??
?
40-49
?
0.??
?
5. The following data give the number of text messages sent on 40 randomly selected days during 2015 by a high school student.
32
33
33
34
35
36
37
37
37
37
38
39
40
41
41
42
42
42
43
44
44
45
45
45
47
47
47
47
47
48
48
49
50
50
51
52
53
54
59
61
Each stem has been displayed (left column). Complete this stem-and-leaf display for these data.
Note: Use a space ...
Business Research
This document contains a summary of statistical analyses conducted on survey data. Key findings include:
- There is a significant relationship between satisfaction in life and both moral standards and religious inclination. These relationships are direct and strong.
- Most ethnic groups who read the Malay language newspaper Utusan Malaysia and Berita Harian are Malay, while most who do not read these are Chinese. Significant relationships were found between ethnicity and reading these newspapers.
- Reliability analyses found the satisfaction in life and religious inclination scales have high reliability, while the moral standards scale's reliability improves after removing two items.
Stats chapter 1
This document provides an overview of different methods for displaying and describing data, including graphs, measures of center, and measures of spread. It discusses bar graphs, pie charts, stem-and-leaf plots, histograms, and calculating the mean, median, quartiles, interquartile range, and standard deviation. Examples are provided using data on football scores to demonstrate these concepts. Key terms like outliers, shape, and transformations of data are also introduced.
Data presentation2019.pptx
This document discusses different methods for presenting data, including mathematical, tabular, and graphical presentation. It provides examples of various types of tables, such as simple frequency distribution tables and class interval frequency distribution tables. It also describes different types of graphs, such as bar charts, pie charts, histograms, line graphs, spot maps, scatter diagrams, and cumulative relative frequency percentage curves. The document aims to help readers understand effective methods for presenting data in a precise and clear manner.
lesson-data-presentation-tools-1.pptx
Descriptive statistics can summarize and graphically present data. Tabular presentations display data in a grid, with tables showing frequencies of categories. Graphical presentations include bar graphs to show frequencies, pie charts to show proportions, and line graphs to show trends over time. Frequency distributions organize raw data into meaningful patterns for analysis by specifying class intervals and calculating frequencies and cumulative frequencies.
Spss cross tab n chi sq bivariate analysis
The document discusses crosstabulation, which shows the relationship between two or more categorical variables through frequency tables. It explains how to compute crosstabs in SPSS by selecting variables for the row and column and choosing relevant statistics like chi-square. The chi-square test determines if the frequencies differ from what is expected by chance alone. It assumes categories are independent and expected counts are at least 5 in each cell.
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- 2. Bar Graphs Steps in Creating a Bar Graph 1. Draw horizontal (x ) and vertical (y) axes 2. Label horizontal and vertical axes Horizontal should always be the count or percentage Vertical should be the groups 3. Equally spaced vertical axis
- 4. Example 1: Here are data on the percent of females among people earning doctorates in 1994 in several fields of study. a) Create a bar graph b) Can you make a pie chart? Why or why not? No, the percents do not add up 100. Computer Science 15.4% Life Sciences 40.7% Education 60.8% Physical Sciences 21.7% Engineering 11.1% Psychology 62.2%
- 5. Example 2: In 1995, there were 90,402 deaths from accidents in the United States. Among these were 43,363 deaths from motor vehicle accidents, 10,483 from falls, 9072 from poisoning, 4350 from drowning, and 4235 from fires. a) Create a chart, show the percentages and include an “other” category b) Create a bar graph based on the percents c) Can you make a pie chart from this data? Why or why not? Yes because your percents add up to 100. Also, each death can be in only 1 category. Accident Count Percent Motor vehicle 43,363 43363/90402 48 Falls 10,483 10483/90402 12 Poisoning 9,072 9072/90402 10 Drowning 4,350 4350/90402 5 Fires 4,235 4235/90402 5 Other 18899 18899/90402 21
Editor's Notes
- Draw in bar graph for marital status data