MAT 243 Milestone Two Guidelines and Rubric
Overview: For your final project, you will assume the role of a data analyst working to analyze and interpret data for the organization described in your assigned
scenario. The scenario information and associated data sets are provided for you in the Final Project Review and Scenario Assignments discussion. In Module
Five, you will complete Milestone Two (Final Project Part II) and submit it for feedback. Note that you do not need the feedback from your earlier milestones to
successfully complete this assignment, so do not delay beginning your work. You should, however, incorporate all the feedback that you receive prior to
delivering the final version of this assignment in Module Seven. Refer to the Final Project Parts I and II Guidelines and Rubric document for more information on
the milestones and the final project delivery schedule.
Like all parts of the final project, this assignment is made up of two components: 1) the Python script that you will develop to perform the required statistical
calculations of the prompt, and 2) an accompanying report in which you will interpret and communicate your results and your understanding of the underlying
statistical concepts. Be sure to review the Milestone Two tutorial video for a detailed walkthrough of the steps and navigation associated with this assignment.
Also, note the opportunity to check your work in Codio by submitting it to the non-graded “Check Its” for automatic feedback prior to submitting your script file
for grading in Brightspace.
Prompt: Specifically, the following critical elements must be addressed:
Part II: Statistical Analysis of Two Samples
I.
II.
Python Script: Navigate to the correct modules in Codio according to your scenario assignment and follow the step-by-step instructions embedded
within. Specifically, you should perform hypothesis tests by creating and executing the appropriate functions in your programming environment.
Summary Report: Use the provided template to create your report.
A. Illustrate the critical parameters that you employed in creating your Python script in Codio. Specify each one and explain their importance for
constructing the confidence intervals and performing the hypothesis tests. Specifically, address the null hypothesis, alternative hypothesis, level
of significance, and associated critical value(s) for the hypothesis test.
B. Interpret the results of your statistical analyses in terms of their statistical significance. Specifically, be sure to address the test statistic and the
probability value of the hypothesis tests.
C. Summarize the results of your statistical analyses and clearly communicate the ideas by translating relevant course concepts and terminology
into plain language.
Rubric
Guidelines for Submission: Your Python script should be submitted following these Codio submission instructions. The summary report should be submitted in
the learning management system as a 2- to 4-page Microsoft Word document (plus a cover page and references) written in APA format. Use double spacing, 12point Times New Roman font, and one-inch margins.
Critical Elements
Proficient (100%)
Needs Improvement (55%)
Not Evident (0%)
Value
Python Script:
Hypothesis Tests
Accurately performs hypothesis
tests by creating and executing
the appropriate functions in the
programming environment
Performs hypothesis tests but
fails to fully or accurately create
and execute the appropriate
functions in the programming
environment
Summary Report:
Illustrate the Critical
Parameters
Illustrates the critical parameters
employed in creating the Python
script, including an explanation
of the importance of each for
performing the hypothesis tests
(85%)
Discusses the critical parameters Does not discuss the critical
employed in creating the Python parameters employed in creating
script, but fails to fully or
the Python script (0%)
accurately illustrate each,
including an explanation of their
importance for performing the
hypothesis tests (55%)
23.5
Summary Report:
Logically interprets the results of
Interpret the Results the statistical analyses in terms
of their statistical significance,
including the test statistic and
the probability value of the
hypothesis tests (85%)
Discusses the results of the
statistical analyses but fails to
fully or logically interpret each
required element in terms of its
statistical significance (55%)
Does not discuss the results of
the statistical analyses (0%)
23.5
Summary Report:
Summarizes the results of the
Clearly Communicate statistical analyses and clearly
communicates all ideas by
translating relevant course
concepts and terminology into
plain language
Summarizes the results of the
statistical analyses but fails to
clearly communicate all ideas by
translating relevant course
concepts and terminology into
plain language
Does not summarize the results
of the statistical analyses
23.5
Submission has major errors
related to citations, grammar,
spelling, syntax, or organization
that negatively impact
readability and articulation of
main ideas
Submission has critical errors
related to citations, grammar,
spelling, syntax, or organization
that prevent understanding of
ideas
5
Articulation of
Response
Submission has no major errors
related to citations, grammar,
spelling, syntax, or organization
Does not perform hypothesis
tests
Total
24.5
100%
5. Part II: Import your Data Set (Scenario C)
Scenario C: Rice Production
If you run into issues and would like to �start over� with a clean copy of the
provided script file (e.g., Milestone2.py), you can click on the �gear� button,
and select �Restore current files� from the drop-down menu.
Recall that you are a quantitative analyst working in an investment fund that is
looking to invest in an agricultural companies that is involved in rice
production. Your primary job is to analyze the production levels of four
candidate companies. Your analysis will help identify companies with rice
production levels that are significantly different than others. This will help
your fund make a data based decision on their investment.
You are now given a task to analyze historical data on rice production for four
agricultural companies. The data consist of monthly rice production in cwt
(Centum Weight - measure of weight) for four companies for the past 21 years.
You will be using this data to finish this task.
Use the following table as a reference guide for the variables of interest for
this project.
Variable
Definition
Company1
Total rice production, in cwt, for Company 1.
Company2
Total rice production, in cwt, for Company 2.
Company3
Total rice production, in cwt, for Company 3.
Company4
Total rice production, in cwt, for Company 4.
Month The Month of the year reported as integers (1, 2, 3, 4, 5, 6, 7, 8, 9, 10,
11, 12).
Step 1: Import your data set
You will be working with the Rice Production data set. To ensure that you
analyze the correct data set, make the following edits to the function
underneath �Step 1: Import your data set� in the Tool Panel on the left side of
the screen.
Uncomment line 11
Replace ???FILE_NAME??? with 'Rice_Production.csv'
Replace ???DATASET_NAME??? with production
6. Part II: Hypothesis Testing for the Difference of Two Population Proportions
(Scenario C)
Step 2: Perform hypothesis test for the difference of two population proportions
(Company1)
It is claimed that the proportion with rice production over 307,200 cwt
(Company1>307200.0) is the same for the month of March (Month=3) and October
(Month=10). Test this claim using a hypothesis test at 1% level of significance.
In order to perform this function, you need to make the appropriate
modifications to the provided script. In other words, you should:
Uncomment lines 15 - 23
Replace ???DATASET_NAME??? with production
Replace '???VARIABLE_NAME???' with the variable 'Company1'
Replace ???Month1??? with the appropriate value
Replace ???Month2??? with the appropriate value
Replace ???Xvalue??? with the appropriate value
Step 3: Perform hypothesis test for the difference of two population proportions
(Company2)
It is claimed that the proportion with rice production over 209,500 cwt
(Company2 > 209500.0) is the same for the month of March (Month=3) and October
(Month=10). Test this claim using a hypothesis test at 1% level of significance.
In order to perform this function, you need to make the appropriate
modifications to the provided script. In other words, you should:
Uncomment lines 27 - 35
Replace ???DATASET_NAME??? with production
Replace '???VARIABLE_NAME???' with the variable 'Company2'
Replace ???Month1??? with the appropriate value
Replace ???Month2??? with the appropriate value
Replace ???Xvalue??? with the appropriate value
7. Part II: Hypothesis Testing for the Difference of Two Population Means
(Scenario C)
Step 4: Perform hypothesis test for the difference of two population means
(Company1)
It is claimed that the rice production for July is not the same as for August.
Test this claim using a hypothesis test at 5% level of significance. In order to
perform this function, you need to make the appropriate modifications to the
provided script. In other words, you should:
Comment lines 15 - 23
Comment lines 27 - 35
Uncomment lines 39 - 43
Replace ???DATASET_NAME??? with production
Replace '???VARIABLE_NAME???' with the variable 'Company1'
Replace ???Month1??? with the appropriate value
Replace ???Month2??? with the appropriate value
Step 5: Perform hypothesis test for the difference of two population means
(Company2)
It is claimed that the rice production for February is more than August. Test
this claim using a hypothesis test at 1% level of significance. In order to
perform this function, you need to make the appropriate modifications to the
provided script. In other words, you should:
Uncomment lines 48 - 52
Replace ???DATASET_NAME??? with production
Replace '???VARIABLE_NAME???' with the variable 'Company2'
Replace ???Month1??? with the appropriate value
Replace ???Month2??? with the appropriate value
8. Part II: Completing Part II (Scenario C)
Step 6: Get your results
Once you have confirmed that your code is correct by passing each of the selfassessments, it is time to get the results of your statistical tests. First, you
must uncomment all of the lines of your scripting file that are not
instructional, as indicated below:
Uncomment lines 15 - 23
Uncomment lines 27 - 35
Uncomment lines 39 - 43
Uncomment lines 48 - 52
DELETE EVERYTHING THAT APPEARS IN RED OR ITALICS
Review the Final Project Parts I and II Guidelines and Rubric document to see how your
summary report will be scored.
Be sure to follow APA format when providing references. If you have questions on APA
formatting, you can check the Purdue OWL website or seek help from the SNHU Writing Lab.
Notes on APA in a Formal Assignment
● Use one-inch margins on all sides.
● Use 12-point Times New Roman font and double-spacing
● Indent the first line of every paragraph by 0.5”.
● Be careful not to use personal pronouns such as “I.”
Be sure to replace all of the text in red or italics with your own writing. (This entire first
page can be deleted after you review the guidelines. Your paper should begin with the title page
that follows.)
MAT-243 Final Project Part II: Summary Report
[Your Name]
Southern New Hampshire University
REMEMBER: DELETE EVERYTHING THAT APPEARS IN RED OR ITALICS
Indicate your response here. In your first paragraph, introduce the subject matter of your
report, identify the data set you used, and provide a brief summary of your experiences and
results in creating and executing the functions in Codio. Use tables whenever you are including
statistics and paragraphs and you are explaining their significance. Include all relevant
citations in APA format (Author last name, Date). If you need to include a graph, include the
image in a one-cell table, as follows:
Diagram : Name of the diagram
In your body paragraph(s), explain the importance of hypothesis tests and how they can
be used in estimating population parameters. Illustrate the critical parameters that you
employed in creating your Python script in Codio. Specify each and explain their importance for
performing the hypothesis tests. Specifically, address each of the following: the null hypothesis,
alternative hypothesis, level of significance, and associated critical value(s) for the hypothesis
test. Identify the variable you used to perform the hypothesis test and the Python functions you
used in your Python script in Codio. Use a table to include the test statistic and the probability
value followed by paragraphs explaining their relevance. The table should look as follows:
Statistics
Value
Test Statistic
9.9999 (Remember to round off to appropriate decimal places.)
Probability Value
0.9999 (Remember to round off to appropriate decimal places.)
Table : Name of the Table
In your final paragraph(s), interpret the results of your analyses in terms of their
statistical significance. Specifically, be sure to address the test statistic and the probability value
of the hypothesis tests. Summarize the results of your statistical analyses and clearly
communicate the ideas by translating relevant course concepts and terminology into plain
language. Include all relevant citations in APA format (Author last name, Date).
References
Zybooks. (2016). Statistics with Python. Los Gatos, CA: Zybooks.
Make sure that you provide appropriate in-text citations in APA style, with the author’s
name and year of publication (Author last name, year). The textbook above is provided as an
example and should be kept in the references section of this paper. Feel free to add other
resources. To add credibility to your paper, remember to cite ALL of the sources within the body
of the paper, as well as in the References section at the end. References should be in alphabetical
order by the author’s last name.
Purchase answer to see full
attachment