Applied Statistics: Summary Report and Python Code 2

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mat243

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Short Summary report and a working python code that goes with it. Attached are the guidelines and rubric, code instructions, and a template for the summary report to make it easier for you.

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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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