9. Part III: Import 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., Milestone3.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 12
Replace '???FILE_NAME???' with 'Rice_Production.csv'
Replace ???DATASET_NAME??? with production
10. Part III: Analysis of Variance (ANOVA) (Scenario C)
Step 2: Analysis of Variance for the difference of five population means
(Company1)
Perform Analysis of Variance to test if rice production levels for May, June,
July, August and September are the different. Use 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:
Uncomment lines 16 - 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 ???Month3??? with the appropriate value
Replace ???Month4??? with the appropriate value
Replace ???Month5??? with the appropriate value
Step 3: Analysis of Variance for the difference of three population means
(Company2)
Perform Analysis of Variance to test if rice production levels for July, August
and September are different. Use 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 28 - 33
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 ???Month3??? with the appropriate value
11. Part III: Boxplots (Scenario C)
Step 4: Plot boxplots for for the difference of five population means (Company1)
Plot boxplots to evaluate any significant differences in rice production levels
for the months of May, June, July, August and September. In order to perform
this function, you need to make the appropriate modifications to the provided
script. In other words, you should:
Comment lines 16 - 23
Comment lines 28 - 33
Uncomment lines 38 - 55
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 ???Month3??? with the appropriate value
Replace ???Month4??? with the appropriate value
Replace ???Month5??? with the appropriate value
Step 5: Plot boxplots for for the difference of three population means
(Company2)
Plot boxplots to evaluate any significant differences in rice production levels
for the months of July, August and September. In order to perform this function,
you need to make the appropriate modifications to the provided script. In other
words, you should:
Uncomment lines 60 - 74
Replace ???DATASET_NAME??? with production
Replace
Replace
Replace
Replace
'???VARIABLE_NAME???'
???Month1??? with the
???Month2??? with the
???Month3??? with the
with the variable 'Company2'
appropriate value
appropriate value
appropriate value
12. Part III: Completing Part III (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 16 - 23
Uncomment lines 28 - 33
Uncomment lines 38 - 55
Uncomment lines 60 - 74
DELETE EVERYTHING THAT APPEARS IN RED OR ITALICS
Review the Final Project Part III 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 III: 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 one-way ANOVA and how it 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
one-way ANOVA. Specifically, address the null hypothesis, alternative hypothesis, level of
significance, associated critical value(s), and probability value(s). Identify the variables that you
used to perform one-way ANOVA tests, 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 and summarize the results of your analyses in terms
of their statistical significance. To further explain the statistical significance of ANOVA, be sure
to include boxplots and identify any significantly different means. Include the boxplot graph as
an image in a one-cell table, as follows:
Diagram : Name of the diagram
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.
MAT 243 Milestone Three 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 Six,
you will complete Milestone Three (Final Project Part III) 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 Eight. Refer to the Final Project Part III Guidelines and Rubric document for more information on the
milestones and 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 Three 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 III: Statistical Analysis of Three or More Samples
I.
II.
Python Script: To complete the tasks listed below, navigate to the correct modules in Codio according to your scenario assignment and follow the stepby-step instructions embedded within each.
A. Perform one-way ANOVA for three or more population means. Calculate the test statistic and probability value by creating and executing the
appropriate functions in your programming environment.
B. Plot boxplots for the means to identify which of the means is significantly different from the others.
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
performing the one-way ANOVA and plotting the boxplots. Specifically, address the null hypothesis, alternative hypothesis, level of significance,
associated critical value, and probability value for one-way ANOVA.
B. Interpret the results of your statistical analyses in terms of their statistical significance. Specifically, be sure to address both one-way ANOVA and
the outputs of your boxplots.
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%)
Python Script: OneWay ANOVA
Accurately performs one-way
ANOVA for three or more
population means, including
calculating the test statistic and
probability value by creating and
executing the appropriate
functions in the programming
environment
Python Script:
Boxplots
Summary Report:
Illustrate the Critical
Parameters
Needs Improvement (55%)
Not Evident (0%)
Performs one-way ANOVA for
Does not perform one-way
three or more population means, ANOVA for three or more
but fails to fully or accurately
population means
calculate the test statistic and
probability value by creating and
executing the appropriate
functions in the programming
environment
Plots boxplots for the means and Plots boxplots for the means but Does not plot boxplots for the
identifies which of the means is fails to fully or accurately do so
means
significantly different from the
others
Illustrates the critical parameters
employed in creating the Python
script, including an explanation
of the importance of each for the
one-way ANOVA and the
boxplots
Value
12.5
12.5
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
accurately illustrate each,
including an explanation of their
importance for the one-way
ANOVA and the boxplots
23
Summary Report:
Logically interprets the results of
Interpret the Results the statistical analyses in terms
of their statistical significance,
including both one-way ANOVA
and the outputs of the boxplots
Discusses the results of the
statistical analyses but fails to
fully or logically interpret each
required element in terms of its
statistical significance
Does not discuss the results of
the statistical analyses
23
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
Articulation of
Response
Submission has no major errors
related to citations, grammar,
spelling, syntax, or organization
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
Total
6
100%
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