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Thx very much for the help, this subject is really not my thing.

Your group has been given a dataset containing 240 records, located in the Student BMtab of this spreadsheet. Each student is only responsible for analyzing 60 of these record records - the specifics of which will be assigned by the instructor. It is important that each student has a unique 60 records, as the results will be an input into the CLC, and duplication of results is not helpful. Note that the data have been randomized, so the data given to your group are likely different than the data given to other groups. The intent of this assignment is for students to organize their data using a pivot table, get a graphical understanding of the data through a bar chart, then do hypothesis testing comparing Bo Diddly Tech results versus the national average All of your analysis should be done in the Student_BM tab of this spreadsheet and submitted as part of the assignmemt. The location where the pivot table, bar chart, and relevant information should be placed in the Student_BM tab is indicated by RED instructions. Once completed, the Student_BM tab will serve as the basis for writing your management report. It is expected that any conclusions you draw in the management report will be consistent with the data and analyses contained in the spreadsheet. Instructions Data Analysis Component: 1. Make a pivot table with: Business Student (Rows), Athlete (Rows), Cheated (Columns), and Cheated (Summed Value). 2. Create a bar chart showing cheating by athletes and business students. 4. Determine if there is a statistical difference between nonathlete BDT business students and the national average for business students as reported by the Chronicle of Higher Education. 5. Determine if there is a statistical difference between athlete BDT business students and the national average for business students as reported by the Chronicle of Higher Education 6. Determine if there is a statistical difference between BDT business students and the national average for business students as reported by the Chronicle of Higher Education. 7. Determine if there is a statistical difference between BDT nonbusiness students and the national average for nonbusiness students as reported by the Chronicle of Higher Education Instructions Data Interpretation Component: Utilizing the data you have analyzed, write a managerial report of 500-800 words to the dean. The managerial report needs to include an introduction, analysis, conclusion, and a minimum of three supporting references. 1. Introduction (Define): Explain in your own words why you are providing this report and the problem(s) you are trying to solve 2. Collect: Describe the data set you used. 3. Organize: Describe your pivot table. 4. Visualize: Include and describe your bar chart. 5. Analyze: Provide a summary of your conclusions based upon the four population proportion hypothesis tests. 6. The Dean has expressed a concem related to the amount of cheating currently taking place at Bo Diddley Tech and has strongly suggested that you tweak the statistical data such that it favors the image of the university. Discuss the potential use of unethical manipulation of statistical data to provide a biased outcome as well as the ethical counter proposal you would offer the dean in this scenario. 7. Conclusion: What advice would you give to the dean based on your analysis of the data? 1. Pivot Table College Athlete Cheated Insert pivot table in this cell - F2 Nationwide Average Business Nonbusiness % Cheated 56% 47% 2. Bar Chart Bar chart starts in this cell - F20 3-6 Hypothesis Test Business Nonathlete vs. National Average Proportion Sample Size (n =count(range) Response of Interest (ROI) Cheated Count for Response (CFR) =COUNTIF(range ROI) Sample Proportion (pbar) =CFR TWU Tall riu." po Ha: p=pol Left Tail HO:p Highlight your HO and Ha po Ha: p na Hypothesized 0.561 Confidence Coefficient (Coe) 0.95 Level of Significance (alpha) 0.05 =1-Coe #DIV/0! #DIV/0! Standard Error (StdError) =SQRT(Hypo*(1-Hypo)n) Test Statistic (Z-stat) =(pbar-Hypo) StdError Accept or Reject: Left Tail Accept or Reject: Right Tail Accept or Reject: Two Tail #DIV/0! =DIV/0! #DIV/0! #DIV/0! #DIV/0! p-value (Lower Tail) =NORM S.DIST(Z TRUE) p-value Upper Tail) =1-Lower Tail p-value (Two Tail) =2*MIN(Lower Tail Upper Tail) Accept or Reject p-value: Left Tail Accept or Reject p-value: Right Tail Accept or Reject p-value: Two Tail #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! p-Lower Limit =pbar-CONFIDENCE.NORM(alpha StdError.n) p-Upper Limit =pbar+CONFIDENCE.NORM(alpha, StdError.n) #DIV/0! thesis testing calculations below based upon your pivot table results. Note the result Business Athlete vs. National Average Proportion Sample Size (1) =count(range) Response of Interest (ROI) Count for Response (CFR) =COUNTIF(range ROI Sample Proportion (pbar) =CFR/ Cheated Two Tail HO: p = po Ha: p=po Left Tail HO: p2 pol Highlight your H0 and Ha Ha:ppol Right Tail HO:p po Ha:p>pol Hypothesized 0.561 Confidence Coefficient (Coe) Level of Significance (alpha) =1-Coe 0.95 0.05 #DIV/0! #DIV/0! DIV/! #DIV/0! #DIV/0! Standard Error (StdError) =SQRT (Hypo (1-Hypo) n) Test Statistic (Z-stat) =(pbar-Hypo) StdError Accept or Reject: Left Tail Accept or Reject: Right Tail Accept or Reject: Two Tail p-value (Lower Tail) ENORM S.DIST(Z TRUE p-value Upper Tail) =l-Lower Tail p-value (Two Tail) =2*MIN(Lower Tail Upper Tail) Accept or Reject p-value: Left Tail Accept or Reject p-value: Right Tail Accept or Reject p-value: Two Tail #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! p-Lower Limit =pbar-CONFIDENCE.NORM(alpha, StdError,n) p-Upper Limit =pbar+CONFIDENCE.NORM(alpha, StdError,n) #DIV/0! Business vs. National Average Proportion Sample Size(n) =count(range) Response of Interest (ROI) Count for Response (CFR) =COUNTIF(range ROI) Sample Proportion (pbar) =CFR Cheated Two Tail HO: p=pol Ha: p=po Left Tail HO: p2 po Highlight your HO and Ha po 0.56 0.95 Hypothesized Confidence Coefficient (Coe) Level of Significance alpha) =1-Coe 0.05 #DIV/0! #DIV/0! Standard Error (StdError) =SQRT (Hypo*(1-Hypo)n) Test Statistic (Z-stat) ={pbar-Hypo) StdError Accept or Reject: Left Tail Accept or Reject: Right Tail Accept or Reject: Two Tail #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! p-value (Lower Tail) ENORM S.DIST(Z TRUE p-value Upper Tail) =l-Lower Tail p-value (Two Tail) =2*MIN(Lower Tail Upper Tail) Accept or Reject p-value: Left Tail Accept or Reject p-value: Right Tail Accept or Reject p-value: Two Tail #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! p-Lower Limit =pbar-CONFIDENCE.NORMalpha, StdError.n) p-Upper Limit =pbar+CONFIDENCE.NORM(alpha, StdError.n) #DIV/0! Nonbusiness vs. National Average Proportion Sample Size (1) =count(range Response of Interest (ROI) Count for Response (CFR) =COUNTIF(range,ROI) Sample Proportion (pbar) =CFRn Cheated Two Tail HO: p= po Ha: p=po Left Tail HO:ppo Highlight your H0 and Ha Ha: p po 0.47 0.95 Hypothesized Confidence Coefficient (Coe) Level of Significance (alpha) =1-Coe 0.05 #DIV/0! #DIV/0! Standard Error (StdError) =SQRT(Hypo*(1-Hypo))n) Test Statistic (Z-stat) = (pbar-Hypo) StdError Accept or Reject: Left Tail Accept or Reject: Right Tail Accept or Reject: Two Tail #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! p-value (Lower Tail) =NORM.S.DIST(Z TRUE) p-value (Upper Tail) =l-Lower Tail p-value (Two Tail) =2*MIN(Lower Tail, UpperTail) Accept or Reject p-value: Left Tail Accept or Reject p-value: Right Tail Accept or Reject p-value: Two Tail #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! p-Lower Limit =pbar-CONFIDENCE NORM(alpha StdError.n) p-Upper Limit =pbar+CONFIDENCE NORM(alpha, StdError,n) #DIV/0! Your group has been given a dataset containing 240 records, located in the Student BMtab of this spreadsheet. Each student is only responsible for analyzing 60 of these record records - the specifics of which will be assigned by the instructor. It is important that each student has a unique 60 records, as the results will be an input into the CLC, and duplication of results is not helpful. Note that the data have been randomized, so the data given to your group are likely different than the data given to other groups. The intent of this assignment is for students to organize their data using a pivot table, get a graphical understanding of the data through a bar chart, then do hypothesis testing comparing Bo Diddly Tech results versus the national average All of your analysis should be done in the Student_BM tab of this spreadsheet and submitted as part of the assignmemt. The location where the pivot table, bar chart, and relevant information should be placed in the Student_BM tab is indicated by RED instructions. Once completed, the Student_BM tab will serve as the basis for writing your management report. It is expected that any conclusions you draw in the management report will be consistent with the data and analyses contained in the spreadsheet. Instructions Data Analysis Component: 1. Make a pivot table with: Business Student (Rows), Athlete (Rows), Cheated (Columns), and Cheated (Summed Value). 2. Create a bar chart showing cheating by athletes and business students. 4. Determine if there is a statistical difference between nonathlete BDT business students and the national average for business students as reported by the Chronicle of Higher Education. 5. Determine if there is a statistical difference between athlete BDT business students and the national average for business students as reported by the Chronicle of Higher Education 6. Determine if there is a statistical difference between BDT business students and the national average for business students as reported by the Chronicle of Higher Education. 7. Determine if there is a statistical difference between BDT nonbusiness students and the national average for nonbusiness students as reported by the Chronicle of Higher Education Instructions Data Interpretation Component: Utilizing the data you have analyzed, write a managerial report of 500-800 words to the dean. The managerial report needs to include an introduction, analysis, conclusion, and a minimum of three supporting references. 1. Introduction (Define): Explain in your own words why you are providing this report and the problem(s) you are trying to solve 2. Collect: Describe the data set you used. 3. Organize: Describe your pivot table. 4. Visualize: Include and describe your bar chart. 5. Analyze: Provide a summary of your conclusions based upon the four population proportion hypothesis tests. 6. The Dean has expressed a concem related to the amount of cheating currently taking place at Bo Diddley Tech and has strongly suggested that you tweak the statistical data such that it favors the image of the university. Discuss the potential use of unethical manipulation of statistical data to provide a biased outcome as well as the ethical counter proposal you would offer the dean in this scenario. 7. Conclusion: What advice would you give to the dean based on your analysis of the data? 1. Pivot Table College Athlete Cheated Insert pivot table in this cell - F2 Nationwide Average Business Nonbusiness % Cheated 56% 47% 2. Bar Chart Bar chart starts in this cell - F20 3-6 Hypothesis Test Business Nonathlete vs. National Average Proportion Sample Size (n =count(range) Response of Interest (ROI) Cheated Count for Response (CFR) =COUNTIF(range ROI) Sample Proportion (pbar) =CFR TWU Tall riu." po Ha: p=pol Left Tail HO:p Highlight your HO and Ha po Ha: p na Hypothesized 0.561 Confidence Coefficient (Coe) 0.95 Level of Significance (alpha) 0.05 =1-Coe #DIV/0! #DIV/0! Standard Error (StdError) =SQRT(Hypo*(1-Hypo)n) Test Statistic (Z-stat) =(pbar-Hypo) StdError Accept or Reject: Left Tail Accept or Reject: Right Tail Accept or Reject: Two Tail #DIV/0! =DIV/0! #DIV/0! #DIV/0! #DIV/0! p-value (Lower Tail) =NORM S.DIST(Z TRUE) p-value Upper Tail) =1-Lower Tail p-value (Two Tail) =2*MIN(Lower Tail Upper Tail) Accept or Reject p-value: Left Tail Accept or Reject p-value: Right Tail Accept or Reject p-value: Two Tail #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! p-Lower Limit =pbar-CONFIDENCE.NORM(alpha StdError.n) p-Upper Limit =pbar+CONFIDENCE.NORM(alpha, StdError.n) #DIV/0! thesis testing calculations below based upon your pivot table results. Note the result Business Athlete vs. National Average Proportion Sample Size (1) =count(range) Response of Interest (ROI) Count for Response (CFR) =COUNTIF(range ROI Sample Proportion (pbar) =CFR/ Cheated Two Tail HO: p = po Ha: p=po Left Tail HO: p2 pol Highlight your H0 and Ha Ha:ppol Right Tail HO:p po Ha:p>pol Hypothesized 0.561 Confidence Coefficient (Coe) Level of Significance (alpha) =1-Coe 0.95 0.05 #DIV/0! #DIV/0! DIV/! #DIV/0! #DIV/0! Standard Error (StdError) =SQRT (Hypo (1-Hypo) n) Test Statistic (Z-stat) =(pbar-Hypo) StdError Accept or Reject: Left Tail Accept or Reject: Right Tail Accept or Reject: Two Tail p-value (Lower Tail) ENORM S.DIST(Z TRUE p-value Upper Tail) =l-Lower Tail p-value (Two Tail) =2*MIN(Lower Tail Upper Tail) Accept or Reject p-value: Left Tail Accept or Reject p-value: Right Tail Accept or Reject p-value: Two Tail #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! p-Lower Limit =pbar-CONFIDENCE.NORM(alpha, StdError,n) p-Upper Limit =pbar+CONFIDENCE.NORM(alpha, StdError,n) #DIV/0! Business vs. National Average Proportion Sample Size(n) =count(range) Response of Interest (ROI) Count for Response (CFR) =COUNTIF(range ROI) Sample Proportion (pbar) =CFR Cheated Two Tail HO: p=pol Ha: p=po Left Tail HO: p2 po Highlight your HO and Ha po 0.56 0.95 Hypothesized Confidence Coefficient (Coe) Level of Significance alpha) =1-Coe 0.05 #DIV/0! #DIV/0! Standard Error (StdError) =SQRT (Hypo*(1-Hypo)n) Test Statistic (Z-stat) ={pbar-Hypo) StdError Accept or Reject: Left Tail Accept or Reject: Right Tail Accept or Reject: Two Tail #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! p-value (Lower Tail) ENORM S.DIST(Z TRUE p-value Upper Tail) =l-Lower Tail p-value (Two Tail) =2*MIN(Lower Tail Upper Tail) Accept or Reject p-value: Left Tail Accept or Reject p-value: Right Tail Accept or Reject p-value: Two Tail #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! p-Lower Limit =pbar-CONFIDENCE.NORMalpha, StdError.n) p-Upper Limit =pbar+CONFIDENCE.NORM(alpha, StdError.n) #DIV/0! Nonbusiness vs. National Average Proportion Sample Size (1) =count(range Response of Interest (ROI) Count for Response (CFR) =COUNTIF(range,ROI) Sample Proportion (pbar) =CFRn Cheated Two Tail HO: p= po Ha: p=po Left Tail HO:ppo Highlight your H0 and Ha Ha: p po 0.47 0.95 Hypothesized Confidence Coefficient (Coe) Level of Significance (alpha) =1-Coe 0.05 #DIV/0! #DIV/0! Standard Error (StdError) =SQRT(Hypo*(1-Hypo))n) Test Statistic (Z-stat) = (pbar-Hypo) StdError Accept or Reject: Left Tail Accept or Reject: Right Tail Accept or Reject: Two Tail #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! p-value (Lower Tail) =NORM.S.DIST(Z TRUE) p-value (Upper Tail) =l-Lower Tail p-value (Two Tail) =2*MIN(Lower Tail, UpperTail) Accept or Reject p-value: Left Tail Accept or Reject p-value: Right Tail Accept or Reject p-value: Two Tail #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! p-Lower Limit =pbar-CONFIDENCE NORM(alpha StdError.n) p-Upper Limit =pbar+CONFIDENCE NORM(alpha, StdError,n) #DIV/0