We would like to introduce sampling software which costs just 10 USD. Sampling is statistical software designed to calculate sampling computation easily such as stratified sampling, cluster sampling, sampling with varying probability and etc. You can download free 7 times running trial license here:
http://www.sampling-software.com
Data > Consolidate provides a way to combine data from two or more ranges of cells into a new range while running one of several functions (such as Sum or Average) on the data. During consolidation, the contents of cells from several sheets can be combined into one place. The effect is that copies of the identified ranges are stacked with their top left corners at the specified result position, and the selected operation is used in each cell to calculate the result value.
Data Analysis
Creating subtotals
Sharing documents
Saving versions
Calc Macros
Data > Consolidate provides a way to combine data from two or more ranges of cells into a new range while running one of several functions (such as Sum or Average) on the data. During consolidation, the contents of cells from several sheets can be combined into one place. The effect is that copies of the identified ranges are stacked with their top left corners at the specified result position, and the selected operation is used in each cell to calculate the result value.
Data Analysis
Creating subtotals
Sharing documents
Saving versions
Calc Macros
For sales data analysis, by creating data breakdowns and filters (example by region, product, salesperson, etc). Objective of Easy Pivot is to provide alternative, easier to understand Pivot Table.
This image appears when a project instruction has changed to accommo.docxjuan1826
This image appears when a project instruction has changed to accommodate an update to
Microsoft 365 Apps
. If the instruction does not match your version of Office, try using the alternate instruction instead.
Open the start file
EX2019-SkillReview-8-1
. The file will be renamed automatically to include your name. Change the project file name if directed to do so by your instructor, and save it.
If the workbook opens in Protected View, click the
Enable Editing
button in the Message Bar at the top of the workbook so you can modify the workbook.
NOTE
: If group titles are not visible on your
Ribbon
in
Excel for Mac
, click the
Excel
menu and select
Preferences
to open the
Excel Preferences
dialog box. Click the
View
button and check the
Group Titles
check box under
In Ribbon, Show
. Close the
Excel Preferences
dialog box.
Use GETPIVOTDATA to extract data from a PivotTable. In cell D1 on the
Analysis
worksheet, display the total annual sales for Ambulatory Care of TX, Inc.
If necessary, go to the
Analysis
worksheet.
Select cell
D1
.
Type
=
Click the
PivotTable
worksheet tab.
Click cell
B4
.
Press
Enter
.
Use consolidate to create a summary of the sales data by region. The summary will be located on the
Analysis
worksheet.
Remain on the
Analysis
worksheet and select cell
A4
.
On the
Data
tab, in the
Data Tools
group, click the
Consolidate
button.
Verify that
Sum
is selected in the
Function
box.
If there are any references in the
All references
box, click each and then click the
-
button to remove them.
Click in the
Reference
box, and then click the
Sales Data
worksheet tab. Click and drag to select cells
C3:E67
.
Click both the
Top row
and
Left column
check boxes.
Click
OK
.
On the
Analysis
worksheet, delete cells
B4:B12
, allowing the other cells to shift left.
Sort the sales data alphabetically by region and then by last name.
Go to the
Sales Data
worksheet, and click any cell in the data set.
On the
Data
tab, in the
Sort & Filter
group, click the
Sort
button.
In the
Sort
dialog, expand the
Sort by
,
Column
list, and select
Region
.
Click the
+
button to add a level.
Expand the
Then by, Column
list, and select
Last Name
.
Click
OK
.
Add subtotals to the data to calculate the total commission earned for each sales associate.
On the
Data
tab, in the
Outline
group, click the
Subtotal
button.
Expand the
At each change in
list, and select
Last Name
.
Verify that
Sum
is selected in the
Use function
box.
Verify that there is a checkmark next to
Commission Earned
in the
Add subtotal to
box.
Click
OK
.
Copy the subtotal data to the
Analysis
worksheet.
On the
Sales Data
worksheet, click the outline level
2
button to collapse the list so only the total commission earned for each sales associate is visible. This will make it easier to copy the data.
Select cells
A3:G77
and copy th.
Week 2 Project - STAT 3001Student Name Type your name here.docxcockekeshia
Week 2 Project - STAT 3001
Student Name: <Type your name here>
Date: <Enter the date on which you began working on this assignment.>
Instructions: To complete this project, you will need the following materials:
· STATDISK User Manual (found in the classroom in DocSharing)
· Access to the Internet to download the STATDISK program.
This assignment is worth a total of 60 points.
Part I. Histograms and Frequency Tables
Instructions
Answers
1. Open the file Diamonds using menu option Datasets and then Elementary Stats, 9th Edition. This file contains some information about diamonds. What are the names of the variables in this file?
2. Create a histogram for the depth of the diamonds using the Auto-fit option. Paste the chart here. Once your histogram displays, click Turn on Labels to get the height of the bars.
3. Using the information in the above histogram, complete this table. Be sure to include frequency, relative frequency, and cumulative frequency.
Depth
Frequency
Relative Frequency
Cumulative Frequency
57-58.9
59-60.9
61-62.9
63-64.9
a. Using the frequency table above, how many of the diamonds have a depth of 60.9 or less? How do you know?
b. Using the frequency table above, how many of the diamonds have a depth between 59 and 62.9? Show your work.
c. What percent of the diamonds have a depth of 61 or more?
Part II. Comparing Datasets
Instructions
Answers
1. Create a boxplot that compares the color and clarity of the diamonds. Paste it here.
2. Describe the similarities and differences in the data sets. Please be specific to the graph created.
Part III. Finding Descriptive Numbers
Instructions
Answers
3. Open the file named Stowaway (using Datasets and then Elementary Stats, 9th Edition). This gives information on the number of stowaways going west vs east.List all the variables in the dataset.
4. Find the Mean, median, and midrange for the Data in Column 1.
5. Find the Range, variance, and standard deviation for the first column.
6. List any values for the first column that you think may be outliers. Why do you think that?
[Hint: You may want to sort the data and look at the smallest and largest values.]
7. Find the Mean, median, and midrange for the data in Column 2.
8. Find the Range, variance, and standard deviation for the data in Column 2.
9. List any values for the second column that you think may be outliers. Why do you think that?
10. Find the five-number summary for the stowaways data in Columns 1 and 2. You will need to label each of the columns with an appropriate measure in the top row for clarity.
11. Compare number of stowaways going west and east using a boxplot of Columns 1 and 2. Paste your boxplot here
12. Create a histogram for the
Column 1 data and paste it here.
13. Create a histogram for the
Column 2 data and paste it here.
Part IV. Interpreting Statistical Information
The Stowaway data contains two columns, both of which are mea.
I am an authorized Consultant for Dukane. This folder contains product information about the AV solutions from Dukane.
Bill McIntosh
Phone :843-442-8888
Email : WKMcIntosh@Comcast.net
PAGE 1Using Microsoft Excel 2010 for Selected Tasks(Thr.docxalfred4lewis58146
PAGE
1
Using Microsoft Excel 2010 for Selected Tasks
(Throughout this document, a set of data refers to observations of just one variable.)
(1) To portray as a bar chart a given frequency, relative frequency, or percentage distribution of a set of qualitative data, one may:
With the categories in one column and the counts or proportions or percentages in another:
1. Select (by clicking-and-dragging) the counts or proportions or percentages.
2. Choose (from upper menu) Insert, then Column (for vertical bars) or Bar (for horizontal bars), then the first pictured sub-type.
3. Right-click on a blank spot in the chart area, choose Select Data…, choose (right of center) Edit, enter the location of the categories, click OK, and click OK.
4. Choose (from upper menu) Layout, then Axis Titles to enter appropriate labels for the horizontal and vertical axes, then Chart Title to enter an appropriate title.
5. If you wish the counts or proportions or percentages to be shown on the bars: Choose (from menu) Data Labels, then your preferred position.
(2)To portray as a pie chart a given frequency, relative frequency, or percentage distribution, one may:
With the categories or numeric classes in one column and the counts or proportions or percentages in another:
1. Select (by clicking-and-dragging) the counts or proportions or percentages.
2. Choose (from upper menu) Insert, then Pie, then the first pictured sub-type.
3. Right-click on a blank spot in the chart area, choose Select Data…, choose (right of center) Edit, enter the location of the categories or numeric classes, click OK, and click OK.
4. (a) Choose (from upper menu) Layout, then Data Labels, then More Data Label Options (which will by default cause each “Value”--i.e, each count or proportion or percentage selected in step 1.--to appear on or near a pie slice); (b) if you wish each category or numeric class to appear on or near a pie slice, select Category name, then your preferred position; (c) click on Close; and (d) if the legend box is now superfluous, delete it.
5. Choose (from menu) Chart Title to enter an appropriate title.
(3) Counting the number of cells (within some range of cells) satisfying a particular condition:
Examples:
· To count how many of the cells A1 through A100 contain the word Agree, one may enter in some blank cell =COUNTIF(A1:A100, “Agree”) Note: In lieu of typing in “Agree”, one may click on a cell containing the word Agree.
· To count how many of the cells A1 through A100 contain the number 89, one may enter in some blank cell =COUNTIF(A1:A100, 89) Note: In lieu of typing in 89, one may click on a cell containing the number 89.
· To count how many of the cells A1 through A100 contain a number in the interval 10 to under 20, enter in some blank cell =COUNTIF(A1:A100,”<20”)-COUNTIF(A1:A100,”<10”)
· Note: Each relative address A1:A100 above may be replaced by the absolute address $A$1:$A$100. In lieu of typing in the absolute address $A$1:$A$100, .
If you have inherited workbooks from
someone else or if you have imported
data from external data sources, you
have probably come across data that
was either structured or formatted (or
both) in such a way that it was either
difficult to read or difficult to work
with. It could be mainframe data that
arrives as all-uppercase letters, dates
that appear in non-date formats,
phone numbers that don’t have dashes
or parentheses, or fields that combine
multiple pieces of data (such as first
names and last names).
Copying Files Across Workbooks Lab 5, Step 1 A. Save al.docxmaxinesmith73660
Copying Files Across Workbooks
Lab 5, Step 1
A. Save all of the wk5_Chap7_cap iLab files to one folder. You should have the
following files:
B. Open the Summary workbook in Excel.
C. Open one of the files you wish to consolidate into this workbook. From the Home tab,
the Cells group, the Format option, select Move or Copy Sheet.
From the Move or Copy dialog box, select the Summary worksheet as location, Move to
End, and Create a Copy:
Click OK.
Copy the Eastside and Westside data in the same way. Your worksheet will now look like
this:
Save this consolidated file as Lab5_yourlastname.xlsx.
Note: Use the Switch Windows command from the View tab to see what is open, and use
the Close button to close all worksheets except the Lab 5 Summary worksheet.
Your Lab 5 Summary worksheet should now look like this:
Creating a Scenario Summary
Lab 6, Step 4
A. Name the cells that will be used in the Scenario Summary.
To use the labels you have already created in the Income Statement, select the two
columns from the Income Statement in the Assumptions area:
In the Formula tab in the Defined Names Group, select “Create from Selection”. Select
the Left column as your name:
Click OK. When you click on the right hand cell, notice that the cell is now named:
Repeat the process and name all of the cells in your Income Statement as you did in the
steps above:
• Tuition per Day
• Food Expenses
• Supplies per Year
• Teacher Cost
• Insurance
• Maintenance
• Administrative & Advertising
• Est. Taxes
• Total Revenue
• Total Expenses
• Net Income (Make sure to also label the net income)
B. Define Scenarios
From the Data tab, click What-If Analysis, and then select Scenario Manager:
The Scenario Manager Dialog Box opens.
Click Add to begin defining your scenarios.
Provide a name in the first textbox:
Now select the cells that will change. You can select multiple cells by holding down the
Control (Ctrl) key as you make your selections. Or you may type a comma after you
select each variable.
Select Number of Children (B6), Teacher Cost (B8), Supplies (B10), and Tuition (B13):
Click OK.
Add the values for your first scenario:
Click OK.
Add your second scenario with the same Changing Cells:
Click OK and then add the Changing Values:
Click OK and then add your final scenario. Name it High and add the values:
To test your scenario, click Show. Your Income Statement will now contain the values
you specified:
Click Close to exit the Scenario Manager.
Change your values back to the original assumptions:
C. Create a Scenario Summary to display the scenarios you have created. Go back to
the Data tab, click What-If Analysis, and then select Scenario Manager:
Click Summary in the Scenario dialog box.
MAT 240 Random Sampling in Excel Tutorial This tutorial wiAbramMartino96
MAT 240 Random Sampling in Excel Tutorial
This tutorial will guide you though the steps necessary to collect a random sample of a data set to put on
a new sheet.
1. Open your data set in Excel. Be sure the Analysis toolpak is enabled. Steps for how to do this are
available on the Microsoft support site.
2. To find a random sample, you first need to insert the =rand() function an empty column next to
your data. In the example being shown, it is column G. To do this, select the target cell and type
in =rand() then press enter.
3. Double click the Fill handle (little square icon) at the bottom right side of the highlighted cell to
copy the formula through to the bottom of the data set. This will copy this formula to each row
of data.
4. Sort your new column to rearrange the data into a random order. To do this, select the data
within your column, then click the Sort & Filter button from the Home ribbon and choose Sort
https://support.microsoft.com/en-us/office/load-the-analysis-toolpak-in-excel-6a63e598-cd6d-42e3-9317-6b40ba1a66b4
Smallest to Largest.
5. A dialog box will open asking if you what you want to do. Select to Expand the selection and
click Sort.
6. Capture your sample size by selecting the amount of rows you are sampling. A sample of 50
would mean you should select the first 50 rows of data.
a. By selecting only the first cell of data in the first column and dragging down, Excel will
count the number of rows for you.
b. Once you have the correct number of rows, then drag to the right to highlight all the
data in the appropriate number of rows.
7. Cut and paste this selected data set onto a new sheet and you will have your random sample
separated from the main data set.
8. In the Descriptive statistics window, select input range field, then select all your numerical data
9. Then check the Summary Statistics box and click ok
10. You now should see a new sheet with just your descriptive statistics listed in a chart. Change the
titles of the columns to their respective names from your data: median listing price, median dollars
per square foot, median square feet. And remove any extraneous information that is not needed for
this project.
MAT 240 Random Sampling in Excel Tutorial
MAT 240 Scatterplots in Excel Tutorial
This tutorial will guide you though the steps necessary to create scatterplots using your data. It will also
walk you through inserting a linear trend line and inserting the regression equation and the R-squared
value on the chart.
1. Open your data set in Excel.
2. Select all the data for the two variables you are targeting. (example: median listing price & Median
square feet)
a. Tip: holding down the CTRL button while selecting your data will allow you to select two
columns of data that are not next to each other
3. On the Insert tab select Recommended Charts button
4. This will bring up the insert chart dialog box prompting you to ...
MAT 240 Random Sampling in Excel Tutorial This tutorial wiAbramMartino96
MAT 240 Random Sampling in Excel Tutorial
This tutorial will guide you though the steps necessary to collect a random sample of a data set to put on
a new sheet.
1. Open your data set in Excel. Be sure the Analysis toolpak is enabled. Steps for how to do this are
available on the Microsoft support site.
2. To find a random sample, you first need to insert the =rand() function an empty column next to
your data. In the example being shown, it is column G. To do this, select the target cell and type
in =rand() then press enter.
3. Double click the Fill handle (little square icon) at the bottom right side of the highlighted cell to
copy the formula through to the bottom of the data set. This will copy this formula to each row
of data.
4. Sort your new column to rearrange the data into a random order. To do this, select the data
within your column, then click the Sort & Filter button from the Home ribbon and choose Sort
https://support.microsoft.com/en-us/office/load-the-analysis-toolpak-in-excel-6a63e598-cd6d-42e3-9317-6b40ba1a66b4
Smallest to Largest.
5. A dialog box will open asking if you what you want to do. Select to Expand the selection and
click Sort.
6. Capture your sample size by selecting the amount of rows you are sampling. A sample of 50
would mean you should select the first 50 rows of data.
a. By selecting only the first cell of data in the first column and dragging down, Excel will
count the number of rows for you.
b. Once you have the correct number of rows, then drag to the right to highlight all the
data in the appropriate number of rows.
7. Cut and paste this selected data set onto a new sheet and you will have your random sample
separated from the main data set.
8. In the Descriptive statistics window, select input range field, then select all your numerical data
9. Then check the Summary Statistics box and click ok
10. You now should see a new sheet with just your descriptive statistics listed in a chart. Change the
titles of the columns to their respective names from your data: median listing price, median dollars
per square foot, median square feet. And remove any extraneous information that is not needed for
this project.
MAT 240 Random Sampling in Excel Tutorial
MAT 240 Scatterplots in Excel Tutorial
This tutorial will guide you though the steps necessary to create scatterplots using your data. It will also
walk you through inserting a linear trend line and inserting the regression equation and the R-squared
value on the chart.
1. Open your data set in Excel.
2. Select all the data for the two variables you are targeting. (example: median listing price & Median
square feet)
a. Tip: holding down the CTRL button while selecting your data will allow you to select two
columns of data that are not next to each other
3. On the Insert tab select Recommended Charts button
4. This will bring up the insert chart dialog box prompting you to ...
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
2. An Introduction to the Sampling Interface
Sampling interface is an interactive software package that uses statistical procedures such
as random sampling, stratified random sampling, one-stage cluster sampling, two-stage
cluster sampling and sampling with varying probability. In general, the software includes a
sampling window. The sampling window consists of two tabs, Data Sheet view and Output
view.
File
A new project is automatically created when the software is launched. You can also open
a new project by clicking File> Add New Project. In general, use the File menu
commands to manage projects.
Open a previously saved project using the File>Open command.
Click File>Open. Use the file browser to find the Sampling (*.sa) project file. By default,
files that can be opened or translated by Sampling are displayed. Then, select the file you
want to open and click Open.
To save an existing, active project with a new name or to a new location:
Click File>Save As. Use the file browser to find the directory where you want to save the
file. Then, type the name of the file in the File name box and click Save.
Use the File>Save command to save the active project.
Display 1: File menu.
3. Inserting Data
The first step is to insert Data into the active project. To enter data right-click in the
window and select Add new column then enter the name for column and press Space or
Enter. After that, you can enter your data. Between data entry, you must press at least one
Space or Enter.
Note1: The columns can have the same name or even can be without a name.
Note2: Some special characters such star, decimal point and minus sign cannot be used for
the column name.
To import datum several times, a panel on the left side of the Data Sheet tab can be used.
The value should be entered in the Value box and the number of iterations should be
entered in the Frequency box and then press Enter or Ok button. For example, in Display
2, two data with value 3 are added to the first column named "a".
The size of writing is determined by the zoom box. The default size is two, the minimum
and maximum allowed values are respectively one and ten.
Display 2: Data Sheet tab.
Edit Data
In the Data Sheet tab, the data and the name of columns cannot be deleted or edited.
However, these advantages can be done by clicking Edit>Edit Column. This opens the
dialogue box shown in Display 3.
4. Display 3: Edit column.
Select the number of the column that you want to edit it by the Column Number box. You
can change the Column’s Name in Column Name box. Also, you can edit or add data to
the specified column in Data box. Finally, click Ok button and the contents of the selected
column will be changed according to the edition.
Moreover, the data can be inserted in the form of fraction or multiplication of two numbers
without spaces in the Data box. For example, if you type 1/5 in the Data box, 0.2 will be
displayed on the main datasheet tab.
Recode into Different Column
Click Edit>Recode into Different Column. This opens the dialogue box shown in
Display 4. You can define values to recode in this dialog box. Select the number of the
column by the Column box. You can specify a name for the new column in the Name
box.
In the Old Value panel, you can specify the type of value that you wish to recode (e.g., a
specific Value, a Range of values, or All Other). All Other can be applied to any value
that not explicitly accounted by the previous recoding rules and it should be applied at the
end.
In the New Value panel, you can specify the new value for column (i.e., a specific numeric
code such as “2,” or copy old values).
In the Old->New panel, click Add button to add the item. The recode that you have
specified appears in Old->New box. If you need to remove one of the recodes that you
have added to the Old->New box, simply click on it and then click the Remove button.
When you have finished defining the conditions, click Ok button.
5. Display 4: Recode into Different Column.
Random Sampling
Click Analyze>Random Sampling. The Random Sampling dialog box is displayed.
This dialogue box is shown in Display 5. Select the columns under the headings
Column(s). If your sample brings with the replacement you should check Sampling with
replacement box in this window and you can determine the size of your statistical society
in the N box. The sample size estimation output is controlled via the Estimation n button
(Display 6). The sample size can be determined to estimate either population mean or
population proportion. The Proportion option is used when the data of the selected
column are 0 and 1.
To obtain an estimator p having probability at least 1 – α of being no farther than d from
the population proportion, the sample size formula based on the normal approximation
gives:
Pr(|p-P|<d) =1- α
) + p(1 − p)]2
/z2
n = Np(1 − p)/[ (N − 1)(d
In the Mean option, you can specify confidence interval in the 2*l box for sample size
estimation. In this procedure the sample mean y is an unbiased estimator of the population
mean μ with variance var( y ) = (N − n) 2
/Nn. Setting:
2 × 𝑠 × 𝑧√
𝑁−𝑛
𝑛𝑁
= 2 × 𝑙
and solving for n gives the necessary sample size:
6. 2 2 2
0
1 1
1 1 1
n
d z N n N
Where
2 2
0 2
z
n
d
. If instead of confidence interval 2*l, you select an amount in r box for
relative error (the difference between the estimate and the true value, divided by the true
value) the criterion to be met is:
Pr(|
(𝑌̅𝑛−𝑌̅ 𝑁)
𝑌̅ 𝑁
|>r) = α
and the sample size formula is:
2 2 2 2
1
1
n
r z N
Display 5: Random Sampling.
7. Display 6: Estimate n.
An output of a command Random Sampling
Display 7 shows the Random Sampling Output, you can see, for example, the mean of
the sample in line 1, the variance of mean in line 2, the confidence interval in line 3, the
sample size in line 4 and the estimation of sample size according to the confidence interval
option in line 5.
Display 7: Output of Random Sampling.
8. Stratified Random Sampling
To select Stratified Random Sampling click Analyze>Stratified Random Sampling.
Display 8 shows the Stratified Random Sampling dialogue box. A source columns list is a
list of columns from the data sheet that can be used in the requested analysis. Each column
is considered as one Stratum.
You can specify the columns under the headings Stratums. Note you should have more
than one Stratum. If sampling is proportional allocation , you should check the
Proportional Allocation box. Then the box N appears above the check box. The size of
the statistical society should be specified in this box.
Display 8: Stratified Random Sampling.
If the sampling is not proportional allocation, after specifying the columns under the
headings Stratums, by double-clicking on the Stratums list, the window will become as
shown in Display 9.
h hn N
n N
9. Display 9: Stratified Random Sampling after double-click.
You should specify the size of statistical society for each stratum and then press Enter or
click Ok button. Finally, click Continue button.
Display 10: Optimum Allocation.
10. The Optimum Allocation output is controlled via the Optimum Allocation button (Display
10). You must specify cost sampling unit for each Stratum and then press Enter or click
Ok button. If the cost of sampling unit for each Stratum is unique, you should check
NEYMAN Allocation and specify an amount of cost.
If an amount of variance is specified, you should select the Variance confirm box and
specify the amount of variance. If an amount of total cost is specified, you should select the
Cost confirm box and specify the amount of cost.
One Stage Cluster Sampling
To select the one-stage cluster sampling click Analyze>One Stage Cluster Sampling.
Display 11 shows the One Stage Cluster Sampling dialogue box.
Display 11: One Stage Cluster Sampling.
A source columns list is a list of columns from the Data sheet that can be used in the
requested analysis. Each column is considered as one Cluster. Total number of clusters
should be determined by the N box and the mean size of clusters should be determined by
the M box. Then click Ok button.
Two Stage Cluster Sampling
The two-stage cluster sampling procedure can be accessed by selecting Analyze >Two
Stage Cluster Sampling. Display 12 shows the Two Stage Cluster Sampling dialogue box.
11. Display 12: Two Stage Cluster Sampling.
A source columns list is a list of columns from the Data sheet that can be used in the
requested analysis. Each column is considered as one Cluster. Total number of Clusters
should be determined by the N box and the mean size of Clusters should be determined by
the M box. If clusters have the same size, you should check Cluster of Equal Sizes.
Otherwise, by double-clicking on the Cluster, the dialog box will become as shown in
Display 13.
12. Display 13: Two Stage Cluster Sampling after double-click.
You should specify the size of statistical society for each cluster and then press Enter or
click Ok button. Then click Continue.
Sampling with Varying Probability
You can proceed to apply the probability sampling with varying by clicking
Analyze>Sampling with Varying Probability. Display 14 shows the Sampling with
varying probability dialogue box.
13. Display 14: Sampling with Varying Probability.
Specify the data columns and the probability of data columns under the headings
Column(s) and probability(s) respectively. Note that the displacement in the columns in
the probability(s) or Column(s) boxes may change the correspondence of the data to their
probability value. If your sample brings without replacement you should check the
Sampling without replacement box and you should determine the size of your statistical
society in the N box.
