Benchmark - Ethical Behavior of Business Students at Bo Diddley Tech

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BoDiddleyTechDataSetKey.xlsx
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Student Instructions BM

Overview - Benchmark College Athlete Cheated Sort <-- First, Sort data from Smallest to Largest
Non_Bus Ath Yes 0.692235172
You and your group has been given a dataset containing 1440 records, located in the Student_BM tab of this spreadsheet. Bus Non_Ath Yes 0.1477297295
Each student is only responsible for analyzing 60 of these record records - the specifics of which will be assigned by the instructor. Non_Bus Non_Ath Yes 0.1352892577
It is important that each student has a unique 60 records, as the results will be an input into the CLC, and duplication of Bus Ath Yes 0.8356235029
results is not helpful. Note that the data have been randomized, so the data given to your group are likely different than the Bus Non_Ath No 0.6910912146
data given to other groups. Non_Bus Non_Ath No 0.9798737062
Non_Bus Ath No 0.5051422105
The intent of this assignment is for students to organize their data using a pivot table, get a graphical understanding Bus Non_Ath No 0.1318733709
of the data through a bar chart, then do hypothesis testing comparing Bo Diddley Tech results versus the national average. Bus Ath Yes 0.220669
Bus Ath Yes 0.8575373641
***Note: First, Sort the data from Smallest to Largest to change the order of the dataset.*** Bus Non_Ath Yes 0.3389846151
Non_Bus Ath No 0.6215536002
All of your analysis should be done in the Student_BM tab of this spreadsheet and submitted as part of the assignmemt. Non_Bus Ath Yes 0.257997253
The locations where the pivot table, bar chart, and relevant information should be placed in the Student_BM tab are Non_Bus Ath Yes 0.4550064497
indicated by RED instructions. Copy the first 60 data points including the labes of Column D, E, and F. Paste data in Student_BM Worsheet Bus Ath Yes 0.0995714894
Bus Ath No 0.8325132369
Once completed, the Student_BM tab will serve as the basis for writing your management report. It is expected that any Non_Bus Non_Ath No 0.8437333047
conclusions you draw in the management report will be consistent with the data and analyses contained in the spreadsheet. Bus Non_Ath Yes 0.1531775332
Non_Bus Ath Yes 0.9617615587
Instructions for Data Analysis Component: Bus Ath Yes 0.1429279751
Non_Bus Ath Yes 0.6531232935
1. Make a pivot table with: Business Student (Rows), Athlete (Rows), Cheated (Columns), and Cheated (Summed Value). Non_Bus Non_Ath No 0.7382068979
Non_Bus Ath Yes 0.8721928826
2. Create a bar chart showing cheating by athletes and business students. Bus Non_Ath Yes 0.5530174952
Non_Bus Ath Yes 0.4420880941
4. Determine if there is a statistical difference between nonathlete BDT business students and the national average for business Non_Bus Ath Yes 0.1214495903
students as reported by the Chronicle of Higher Education. Non_Bus Non_Ath Yes 0.4033089744
Bus Non_Ath No 0.1036441272
5. Determine if there is a statistical difference between athlete BDT business students and the national average for business Non_Bus Ath No 0.0666437393
students as reported by the Chronicle of Higher Education. Bus Ath Yes 0.2625236238
Bus Ath No 0.0656776338
6. Determine if there is a statistical difference between BDT business students and the national average for business students Non_Bus Non_Ath Yes 0.9647239894
as reported by the Chronicle of Higher Education. Bus Ath Yes 0.152436333
Bus Ath No 0.9341312536
7. Determine if there is a statistical difference between BDT nonbusiness students and the national average for nonbusiness Non_Bus Non_Ath No 0.6243300755
students as reported by the Chronicle of Higher Education. Non_Bus Ath No 0.7893064476
Non_Bus Ath No 0.4691500426
Bus Ath Yes 0.5593968686
Instructions for Data Interpretation Component: Bus Non_Ath No 0.3768807721
Non_Bus Ath No 0.3028585086
Utilizing the data you have analyzed, write a managerial report of 500-800 words to the dean. The managerial report needs to Bus Non_Ath Yes 0.7664403994
include an introduction, analysis, conclusion, and a minimum of three supporting references. Non_Bus Ath No 0.0381309134
Non_Bus Non_Ath No 0.5500401536
1. Introduction (Define): Explain, in your own words, why you are providing this report and the problem(s) you are trying to solve. Bus Ath Yes 0.2891315924
Bus Ath Yes 0.5212439715
2. Collect: Describe the data set you used. Bus Non_Ath Yes 0.3084625559
Non_Bus Ath No 0.9106517304
3. Organize: Describe your pivot table. Bus Ath Yes 0.4651078517
Bus Non_Ath Yes 0.898065428
4. Visualize: Include and describe your bar chart. Bus Non_Ath No 0.551227394
Bus Ath No 0.7789533395
5. Analyze: Provide a summary of your conclusions based upon the four population proportion hypothesis tests. Bus Non_Ath Yes 0.9685596087
Non_Bus Ath Yes 0.6215394651
6. The dean has expressed a concern related to the amount of cheating currently taking place at Bo Diddley Tech and has strongly Bus Ath No 0.7739781104
suggested that you "tweak" the statistical data such that they favor the image of the university. Bus Ath No 0.6984346676
Discuss the potential use of unethical manipulation of statistical data to provide a biased outcome as well as the ethical counter Non_Bus Non_Ath Yes 0.3531075953
proposal you would offer the dean in this scenario. Bus Non_Ath No 0.7446084587
Non_Bus Ath No 0.9737248624
7. Conclusion: What advice would you give to the dean based upon your analysis of the data? Bus Non_Ath No 0.3743720719
Bus Non_Ath Yes 0.6850206403
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Bus Ath Yes 0.0962344907
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Bus Ath Yes 0.2704599006
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Non_Bus Non_Ath Yes 0.8396875974
Non_Bus Ath No 0.3331060065
Non_Bus Non_Ath Yes 0.2764768259
Bus Ath No 0.2892275502
Bus Non_Ath Yes 0.4469081863
Non_Bus Ath No 0.0393636754
Bus Non_Ath Yes 0.521149159
Non_Bus Ath Yes 0.48534245
Bus Non_Ath Yes 0.4381033131
Non_Bus Ath No 0.4302151138
Bus Non_Ath Yes 0.3644851364
Bus Ath No 0.0580727958
Non_Bus Non_Ath No 0.5658524884
Non_Bus Ath Yes 0.7528464604
Non_Bus Non_Ath No 0.9999131469
Bus Ath No 0.9036223842
Non_Bus Ath Yes 0.6454971023
Bus Non_Ath No 0.8538818097
Non_Bus Ath Yes 0.0681757799
Bus Ath Yes 0.8274253769
Non_Bus Non_Ath Yes 0.4991553748
Bus Ath No 0.7333886345
Non_Bus Ath No 0.1250721854
Bus Ath Yes 0.8416319499
Non_Bus Non_Ath No 0.0683366098
Non_Bus Ath Yes 0.2771610318
Bus Ath No 0.708114226
Bus Ath Yes 0.0132130107
Bus Non_Ath Yes 0.4608770234
Bus Ath No 0.7598251214
Non_Bus Ath No 0.8278144362
Bus Non_Ath Yes 0.5471739892
Non_Bus Non_Ath No 0.4524004084
Non_Bus Ath No 0.5024432347
Bus Non_Ath Yes 0.0982883057
Bus Ath Yes 0.1771220904
Non_Bus Ath Yes 0.1227574078
Non_Bus Non_Ath No 0.4774724041
Bus Ath No 0.8252556297
Non_Bus Non_Ath No 0.7962758844
Non_Bus Non_Ath Yes 0.5108391667
Bus Non_Ath Yes 0.4432822191
Non_Bus Non_Ath No 0.6707370085
Non_Bus Non_Ath No 0.9674548236
Bus Non_Ath Yes 0.7229896994
Non_Bus Ath No 0.4539471706
Non_Bus Ath No 0.8216356645
Bus Ath Yes 0.7770616819
Bus Non_Ath Yes 0.3798622018
Non_Bus Ath Yes 0.8357029889
Non_Bus Non_Ath Yes 0.9868918428
Non_Bus Non_Ath No 0.8279554181
Non_Bus Ath Yes 0.3125751792
Bus Non_Ath Yes 0.4199702254
Bus Ath Yes 0.9571351903
Non_Bus Ath Yes 0.175642434
Bus Non_Ath No 0.9388219969
Bus Non_Ath Yes 0.4843372384
Non_Bus Ath Yes 0.2577465662
Bus Non_Ath No 0.6918880541
Bus Ath Yes 0.4604859989
Non_Bus Ath Yes 0.1479650997
Bus Ath No 0.88999856
Non_Bus Non_Ath Yes 0.3831350613
Non_Bus Ath Yes 0.4134309294
Bus Non_Ath No 0.6575102906
Non_Bus Ath Yes 0.2344249854
Bus Ath No 0.451448693
Non_Bus Non_Ath Yes 0.8984583561
Non_Bus Non_Ath No 0.5565374945
Bus Ath No 0.1530265144
Bus Non_Ath Yes 0.9625872026
Non_Bus Ath Yes 0.2912598715
Bus Non_Ath Yes 0.0960580702
Bus Non_Ath Yes 0.0505070539
Bus Non_Ath Yes 0.0323530486
Non_Bus Non_Ath No 0.789161496
Bus Non_Ath Yes 0.2979844948
Bus Non_Ath Yes 0.7264448476
Non_Bus Non_Ath No 0.4403106876
Non_Bus Non_Ath No 0.4435380548
Non_Bus Ath No 0.3340836656
Bus Ath Yes 0.3089781556
Bus Non_Ath No 0.2663034201
Non_Bus Non_Ath Yes 0.2757530823
Bus Ath Yes 0.4919843052
Non_Bus Ath No 0.4148255301
Bus Ath No 0.8443034448
Bus Non_Ath Yes 0.6878186208
Bus Non_Ath Yes 0.8100460273
Bus Ath Yes 0.3220020899
Non_Bus Ath No 0.5063777047
Non_Bus Ath Yes 0.5193161906
Bus Non_Ath Yes 0.3268520481
Bus Non_Ath Yes 0.8728246599
Bus Non_Ath Yes 0.1868386207
Non_Bus Ath Yes 0.2002697349
Non_Bus Ath Yes 0.5366577384
Bus Ath Yes 0.5055691794
Bus Ath Yes 0.325234869
Non_Bus Non_Ath No 0.7428515614
Non_Bus Non_Ath Yes 0.0919491346
Bus Ath No 0.0646668797
Non_Bus Ath Yes 0.0573443211
Non_Bus Non_Ath Yes 0.079055866
Non_Bus Ath No 0.1454078147
Non_Bus Non_Ath Yes 0.7434926641
Non_Bus Non_Ath Yes 0.6360503718
Non_Bus Ath No 0.4958262188
Bus Non_Ath Yes 0.5951516345
Bus Ath Yes 0.5824658737
Non_Bus Ath Yes 0.6672207116
Non_Bus Non_Ath No 0.819387261
Bus Ath No 0.1287097273
Non_Bus Ath No 0.3047010972
Non_Bus Non_Ath No 0.12967953
Non_Bus Ath No 0.1098639491
Non_Bus Non_Ath Yes 0.4239585582
Non_Bus Non_Ath Yes 0.7375774923
Non_Bus Non_Ath Yes 0.5922841913
Bus Non_Ath Yes 0.3826393211
Bus Non_Ath Yes 0.1449691474
Bus Ath Yes 0.6229637556
Bus Non_Ath No 0.5538040714
Bus Non_Ath Yes 0.809259376
Non_Bus Non_Ath Yes 0.4844020439
Bus Ath No 0.0214104384
Bus Ath Yes 0.1654574378
Non_Bus Non_Ath Yes 0.4494742772
Non_Bus Ath No 0.1948980563
Non_Bus Ath No 0.1578358559
Bus Ath No 0.2057139726
Bus Non_Ath Yes 0.6275153526
Non_Bus Non_Ath Yes 0.185557429
Non_Bus Ath Yes 0.1135275031
Non_Bus Non_Ath No 0.8730425909
Non_Bus Non_Ath No 0.1515472814
Non_Bus Non_Ath Yes 0.8945082241
Non_Bus Non_Ath Yes 0.1074391211
Bus Non_Ath Yes 0.5300611577
Bus Ath Yes 0.3803461039
Bus Ath No 0.0124628013
Bus Non_Ath Yes 0.9752305421
Non_Bus Non_Ath Yes 0.7053481988
Non_Bus Ath Yes 0.0080907938
Bus Non_Ath Yes 0.5777069034
Bus Non_Ath Yes 0.2023768353
Non_Bus Ath No 0.824509586
Non_Bus Non_Ath Yes 0.9916129272
Non_Bus Ath Yes 0.5704849629
Non_Bus Non_Ath No 0.8297313501
Non_Bus Ath No 0.7982083481
Non_Bus Ath Yes 0.4681498282
Non_Bus Non_Ath No 0.3600562298
Non_Bus Non_Ath Yes 0.4157792645
Bus Ath No 0.0662417493
Non_Bus Non_Ath Yes 0.5662662527
Non_Bus Ath Yes 0.7084089026
Non_Bus Ath Yes 0.3309710871
Bus Non_Ath Yes 0.9265427463
Bus Ath No 0.2899533336
Non_Bus Non_Ath No 0.8688268612
Non_Bus Non_Ath Yes 0.1752044228
Bus Ath Yes 0.2447872912
Non_Bus Ath Yes 0.6854479538
Non_Bus Ath Yes 0.7140384857
Non_Bus Ath Yes 0.3465647792
Bus Non_Ath Yes 0.673495931
Non_Bus Ath Yes 0.330167954
Non_Bus Ath Yes 0.8643295131
Bus Non_Ath Yes 0.9668298271
Non_Bus Non_Ath Yes 0.9301707458
Non_Bus Non_Ath No 0.0908282114
Bus Non_Ath Yes 0.7269692576
Non_Bus Non_Ath No 0.820830831
Bus Ath No 0.9178711226
Bus Non_Ath Yes 0.0049893375
Non_Bus Non_Ath No 0.9203463839
Non_Bus Non_Ath No 0.2898270923
Bus Non_Ath Yes 0.2236519845
Bus Non_Ath Yes 0.6545474483
Non_Bus Non_Ath Yes 0.7929036695
Bus Non_Ath Yes 0.9863870031
Bus Non_Ath Yes 0.1204680569
Bus Non_Ath Yes 0.4644824631
Bus Ath Yes 0.7580249488
Non_Bus Ath Yes 0.4806276298
Non_Bus Ath No 0.407772596
Non_Bus Non_Ath No 0.016109847
Bus Non_Ath No 0.0560839828
Non_Bus Ath No 0.7817598652
Bus Ath No 0.2652136512
Non_Bus Non_Ath Yes 0.184221879
Non_Bus Non_Ath Yes 0.4277850423
Non_Bus Ath No 0.4241449058
Non_Bus Non_Ath No 0.6692733596
Bus Ath No 0.2938270146
Bus Ath Yes 0.7872565372
Non_Bus Non_Ath No 0.906855774
Non_Bus Non_Ath Yes 0.0823354599
Non_Bus Ath Yes 0.7156858673
Bus Ath Yes 0.9947393575
Bus Ath Yes 0.1431426188
Bus Non_Ath Yes 0.5176031812
Bus Ath Yes 0.3286380447
Non_Bus Non_Ath Yes 0.0963195721
Bus Ath Yes 0.1300178781
Non_Bus Non_Ath Yes 0.5123812892
Non_Bus Ath No 0.0020424069
Non_Bus Non_Ath No 0.4374756071
Bus Non_Ath Yes 0.343379123
Non_Bus Non_Ath No 0.7871813206
Bus Non_Ath Yes 0.2183490096
Bus Non_Ath Yes 0.3379299486
Bus Non_Ath Yes 0.4691922163
Non_Bus Non_Ath No 0.0945742354
Non_Bus Non_Ath No 0.1312898138
Bus Ath No 0.4546426998
Bus Ath Yes 0.8857035627
Bus Non_Ath Yes 0.4801656722
Bus Ath Yes 0.1243512828
Non_Bus Non_Ath No 0.2924550206
Bus Ath Yes 0.4822726718
Bus Ath Yes 0.3998128676
Bus Ath No 0.5820085166
Bus Ath Yes 0.6544580391
Non_Bus Ath No 0.2215180447
Non_Bus Ath Yes 0.2043754226
Non_Bus Non_Ath Yes 0.0247884464
Bus Non_Ath Yes 0.3183547646
Non_Bus Non_Ath Yes 0.3749965753
Non_Bus Non_Ath Yes 0.7262615159
Bus Ath No 0.2558385323
Non_Bus Ath No 0.211203142
Bus Non_Ath Yes 0.8079937303
Bus Non_Ath Yes 0.7233524948
Bus Ath No 0.8092360022
Bus Ath No 0.6949897461
Bus Ath Yes 0.6447460862
Bus Non_Ath Yes 0.8403044859
Non_Bus Ath No 0.3297006063
Non_Bus Non_Ath No 0.4579419027
Non_Bus Non_Ath No 0.7683777938
Non_Bus Non_Ath No 0.8205490334
Non_Bus Non_Ath Yes 0.1946279475
Non_Bus Ath Yes 0.8740681476
Bus Ath Yes 0.9807421601
Non_Bus Non_Ath Yes 0.050530795
Bus Non_Ath Yes 0.6961012212
Non_Bus Non_Ath Yes 0.7407866358
Bus Ath Yes 0.472541251
Non_Bus Ath Yes 0.7969863113
Bus Ath Yes 0.3069488025
Bus Non_Ath Yes 0.9428985874
Non_Bus Non_Ath Yes 0.205221446
Bus Non_Ath Yes 0.3029596509
Non_Bus Non_Ath Yes 0.6737443568
Non_Bus Non_Ath Yes 0.9200689738
Bus Non_Ath Yes 0.5830649395
Bus Ath Yes 0.7553609069
Bus Ath Yes 0.7339885666
Bus Ath No 0.9704167547
Bus Ath Yes 0.0363716241
Bus Ath Yes 0.6428667287
Non_Bus Non_Ath Yes 0.0844343657
Non_Bus Ath Yes 0.885531305
Bus Non_Ath Yes 0.1993561722

Student_BM

College Athlete Cheated 1. Pivot Table Nationwide Average % Cheated
Insert pivot table in this cell - F2 Business 56%
Nonbusiness 47%
2. Bar Chart
Bar chart starts in this cell - F20
Insert the appropriate numbers into the hypothesis testing calculations below based upon your pivot table results. Note the results.
3-6 Hypothesis Test
Business Nonathlete vs. National Average Business Athlete vs. National Average Business vs. National Average Nonbusiness vs. National Average
Proportion Proportion Proportion Proportion
Sample Size (n) =count(range) Sample Size (n) =count(range) Sample Size (n) =count(range) Sample Size (n) =count(range)
Response of Interest (ROI) Cheated Response of Interest (ROI) Cheated Response of Interest (ROI) Cheated Response of Interest (ROI) Cheated
Count for Response (CFR) =COUNTIF(range,ROI) Count for Response (CFR) =COUNTIF(range,ROI) Count for Response (CFR) =COUNTIF(range,ROI) Count for Response (CFR) =COUNTIF(range,ROI)
Sample Proportion (pbar) =CFR/n Sample Proportion (pbar) =CFR/n Sample Proportion (pbar) =CFR/n Sample Proportion (pbar) =CFR/n
Highlight your H0 and Ha Two Tail H0: p = po Ha: p ≠ po Left Tail H0: p ≥ po Ha: p < po Right Tail H0: p ≤ po Ha: p > po Highlight your H0 and Ha Two Tail H0: p = po Ha: p ≠ po Left Tail H0: p ≥ po Ha: p < po Right Tail H0: p ≤ po Ha: p > po Highlight your H0 and Ha Two Tail H0: p = po Ha: p ≠ po Left Tail H0: p ≥ po Ha: p < po Right Tail H0: p ≤ po Ha: p > po Highlight your H0 and Ha Two Tail H0: p = po Ha: p ≠ po Left Tail H0: p ≥ po Ha: p < po Right Tail H0: p ≤ po Ha: p > po
Hypothesized 0.56 Hypothesized 0.56 Hypothesized 0.56 Hypothesized 0.47
Confidence Coefficient (Coe) 0.95 Confidence Coefficient (Coe) 0.95 Confidence Coefficient (Coe) 0.95 Confidence Coefficient (Coe) 0.95
Level of Significance (alpha) =1-Coe 0.05 Level of Significance (alpha) =1-Coe 0.05 Level of Significance (alpha) =1-Coe 0.05 Level of Significance (alpha) =1-Coe 0.05
Standard Error (StdError) =SQRT(Hypo*(1-Hypo)/n) ERROR:#DIV/0! Standard Error (StdError) =SQRT(Hypo*(1-Hypo)/n) ERROR:#DIV/0! Standard Error (StdError) =SQRT(Hypo*(1-Hypo)/n) ERROR:#DIV/0! Standard Error (StdError) =SQRT(Hypo*(1-Hypo)/n) ERROR:#DIV/0!
Test Statistic (Z-stat) =(pbar-Hypo)/StdError ERROR:#DIV/0! Test Statistic (Z-stat) =(pbar-Hypo)/StdError ERROR:#DIV/0! Test Statistic (Z-stat) =(pbar-Hypo)/StdError ERROR:#DIV/0! Test Statistic (Z-stat) =(pbar-Hypo)/StdError ERROR:#DIV/0!
Accept or Reject: Left Tail ERROR:#DIV/0! Accept or Reject: Left Tail ERROR:#DIV/0! Accept or Reject: Left Tail ERROR:#DIV/0! Accept or Reject: Left Tail ERROR:#DIV/0!
Accept or Reject: Right Tail ERROR:#DIV/0! Accept or Reject: Right Tail ERROR:#DIV/0! Accept or Reject: Right Tail ERROR:#DIV/0! Accept or Reject: Right Tail ERROR:#DIV/0!
Accept or Reject: Two Tail ERROR:#DIV/0! Accept or Reject: Two Tail ERROR:#DIV/0! Accept or Reject: Two Tail ERROR:#DIV/0! Accept or Reject: Two Tail ERROR:#DIV/0!
p-value (Lower Tail) =NORM.S.DIST(z,TRUE) ERROR:#DIV/0! p-value (Lower Tail) =NORM.S.DIST(z,TRUE) ERROR:#DIV/0! p-value (Lower Tail) =NORM.S.DIST(z,TRUE) ERROR:#DIV/0! p-value (Lower Tail) =NORM.S.DIST(z,TRUE) ERROR:#DIV/0!
p-value (Upper Tail) =1-LowerTail ERROR:#DIV/0! p-value (Upper Tail) =1-LowerTail ERROR:#DIV/0! p-value (Upper Tail) =1-LowerTail ERROR:#DIV/0! p-value (Upper Tail) =1-LowerTail ERROR:#DIV/0!
p-value (Two Tail) =2*MIN(LowerTail,UpperTail) ERROR:#DIV/0! p-value (Two Tail) =2*MIN(LowerTail,UpperTail) ERROR:#DIV/0! p-value (Two Tail) =2*MIN(LowerTail,UpperTail) ERROR:#DIV/0! p-value (Two Tail) =2*MIN(LowerTail,UpperTail) ERROR:#DIV/0!
Accept or Reject p-value: Left Tail ERROR:#DIV/0! Accept or Reject p-value: Left Tail ERROR:#DIV/0! Accept or Reject p-value: Left Tail ERROR:#DIV/0! Accept or Reject p-value: Left Tail ERROR:#DIV/0!
Accept or Reject p-value: Right Tail ERROR:#DIV/0! Accept or Reject p-value: Right Tail ERROR:#DIV/0! Accept or Reject p-value: Right Tail ERROR:#DIV/0! Accept or Reject p-value: Right Tail ERROR:#DIV/0!
Accept or Reject p-value: Two Tail ERROR:#DIV/0! Accept or Reject p-value: Two Tail ERROR:#DIV/0! Accept or Reject p-value: Two Tail ERROR:#DIV/0! Accept or Reject p-value: Two Tail ERROR:#DIV/0!
p-Lower Limit =pbar-CONFIDENCE.NORM(alpha,StdError,n) ERROR:#DIV/0! p-Lower Limit =pbar-CONFIDENCE.NORM(alpha,StdError,n) ERROR:#DIV/0! p-Lower Limit =pbar-CONFIDENCE.NORM(alpha,StdError,n) ERROR:#DIV/0! p-Lower Limit =pbar-CONFIDENCE.NORM(alpha,StdError,n) ERROR:#DIV/0!
p-Upper Limit =pbar+CONFIDENCE.NORM(alpha,StdError,n) ERROR:#DIV/0! p-Upper Limit =pbar+CONFIDENCE.NORM(alpha,StdError,n) ERROR:#DIV/0! p-Upper Limit =pbar+CONFIDENCE.NORM(alpha,StdError,n) ERROR:#DIV/0! p-Upper Limit =pbar+CONFIDENCE.NORM(alpha,StdError,n) ERROR:#DIV/0!

Student Instructions CLC

Overview - Benchmark
You and your group has been given a data set containing 1440 records, located in the Student_BM tab of this spreadsheet. As part of
benchmark assignment, you reached various conclusions based upon data sets of 60 records. Now here in the CLC portion,
your group will recreate the pivot table, bar graph, and hypothesis tests. But this time all your member's data records will be used, not just
60 records. Also, an additional hypothesis test has been added comparing samples taken at Bo Diddley Tech against each other,
not just against the national standard. Finally, a 2 x 2 test of independence has been added.
The intent of the CLC assignment is to provide insight into the value of larger data sets, and to determine if conclusions reached
with the 60 record data sets hold up when more data are available for analysis.
Similar to the benchmark assignment, all your group's analysis should be done in the Student_CLC tab of this spreadsheet and
submitted as part of the assignment. The locations where the pivot table, bar chart, and relevant hypothesis test and TOI
information should be placed are in the Student_CLC tab indicated by RED instructions.
Once completed, the Student_CLC tab will serve as the basis for preparing your management presentation. It is expected that any
conclusions you draw in the management presentation will be consistent with the data and analyses contained in the spreadsheet.
Instructions for Data Analysis Component:
Submit the group's Excel data calculations (Alpha 0.05).
The full data set will include each student's combined dataset. This combined dataset will be the basis for all CLC calculations and analysis.
1. Each group member should refresh their memories regarding the conclusions they reached on the benchmark assignment.
2. As a group, make a pivot table with: Business Student (Rows), Athlete (Rows), Cheated (Columns), and Cheated (Summed Value).
3. As a group, 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.
8. Determine if there is a statistical difference between BDT business student athletes and nonathletes.
9. Determine if there is a statistical difference among business students, nonbusiness students, athletes and nonathletes at BDT
by conducting a 2x2 chi-square test of independence.
Instructions for Data Interpretation Component:
As a group, prepare and submit one group PowerPoint presentation (8-12 slides) based upon the analysis and conclusions from
the group's analysis of all combined data records. It should include the following (Include Speaker Notes):
1. Introduction Slide (Define): Include Loom link.
2. Collect Slide: Describe the data set you used.
3. Organize Slide: Include your pivot table.
4. Visualize Slide: Include and describe your bar chart.
5. Analyze Slides: Provide a summary of your conclusions based upon the five population proportion hypothesis tests and test of
independence.
6. Ethical Summary Slide : The dean has expressed concern related to the amoung of cheating at Bo Diddley Tech and has
strongly suggested that you "tweak" the statistical data such that it favors the image of the university. In one slide, 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.
7. Conclusion Slide(s): Describe your conclusions and recommendations to the dean.
After creating your group PowerPoint, create a video presentation (4-5 minutes) that showcases each of the required
elements. Professional business attire is expected. Each group member must record video and present one of the required elements.

Student_CLC

College Athlete Cheated 1. Pivot Table Nationwide Average % Cheated
Insert pivot table in this cell - F2 Business 56%
Nonbusiness 47%
2. Bar Chart
Bar chart starts in this cell - F20
Insert the appropriate numbers into the hypothesis testing calculations below based upon your pivot table results. Note the results.
3-7 Hypothesis Test
Business Nonathlete vs. National Average Business Athlete vs. National Average Business vs. National Average Nonbusiness vs. National Average Business Athlete vs. Business Nonathlete
Proportion Proportion Proportion Proportion p1 and p2 Proportion
Sample Size (n) =count(range) Sample Size (n) =count(range) Sample Size (n) =count(range) Sample Size (n) =count(range) Athlete Nonathlete
Response of Interest (ROI) Cheated Response of Interest (ROI) Cheated Response of Interest (ROI) Cheated Response of Interest (ROI) Cheated Sample Size (n1 or n2) =COUNT(range)
Count for Response (CFR) =COUNTIF(range,ROI) Count for Response (CFR) =COUNTIF(range,ROI) Count for Response (CFR) =COUNTIF(range,ROI) Count for Response (CFR) =COUNTIF(range,ROI) Response of Interest (ROI)
Sample Proportion (pbar) =CFR/n Sample Proportion (pbar) =CFR/n Sample Proportion (pbar) =CFR/n Sample Proportion (pbar) =CFR/n Count for Response (CFR) =COUNTIF(n1or2,ROI)
Sample Proportion (p1 or p2) =CFR1or2/n1or2 ERROR:#DIV/0! ERROR:#DIV/0!
Highlight your H0 and Ha Two Tail H0: p = po Ha: p ≠ po Left Tail H0: p ≥ po Ha: p < po Right Tail H0: p ≤ po Ha: p > po Highlight your H0 and Ha Two Tail H0: p = po Ha: p ≠ po Left Tail H0: p ≥ po Ha: p < po Right Tail H0: p ≤ po Ha: p > po Highlight your H0 and Ha Two Tail H0: p = po Ha: p ≠ po Left Tail H0: p ≥ po Ha: p < po Right Tail H0: p ≤ po Ha: p > po Highlight your H0 and Ha Two Tail H0: p = po Ha: p ≠ po Left Tail H0: p ≥ po Ha: p < po Right Tail H0: p ≤ po Ha: p > po
Hypothesized 0.56 Hypothesized 0.56 Hypothesized 0.56 Hypothesized 0.47 Highlight your H0 and Ha Two Tail H0: p1-p2=0 Left Tail H0: p1-p2≥0 Right Tail H0: p1-p2≤0 Ha: p1-p2≠0 Ha: p1-p2<0 Ha: p1-p2>0
Confidence Coefficient (Coe) 0.95 Confidence Coefficient (Coe) 0.95 Confidence Coefficient (Coe) 0.95 Confidence Coefficient (Coe) 0.95 Hypothesized Value 0
Level of Significance (alpha) =1-Coe 0.05 Level of Significance (alpha) =1-Coe 0.05 Level of Significance (alpha) =1-Coe 0.05 Level of Significance (alpha) =1-Coe 0.05 Level of Sig. α 0.05
Point Estimation of Difference (Point) =p1-p2 ERROR:#DIV/0!
Standard Error (StdError) =SQRT(Hypo*(1-Hypo)/n) ERROR:#DIV/0! Standard Error (StdError) =SQRT(Hypo*(1-Hypo)/n) ERROR:#DIV/0! Standard Error (StdError) =SQRT(Hypo*(1-Hypo)/n) ERROR:#DIV/0! Standard Error (StdError) =SQRT(Hypo*(1-Hypo)/n) ERROR:#DIV/0!
Test Statistic (Z-stat) =(pbar-Hypo)/StdError ERROR:#DIV/0! Test Statistic (Z-stat) =(pbar-Hypo)/StdError ERROR:#DIV/0! Test Statistic (Z-stat) =(pbar-Hypo)/StdError ERROR:#DIV/0! Test Statistic (Z-stat) =(pbar-Hypo)/StdError ERROR:#DIV/0! Pooled Estimation of p (PE) =(n1*p1+n2*p2)/(n1+n2) ERROR:#DIV/0!
Accept or Reject: Left Tail ERROR:#DIV/0! Accept or Reject: Left Tail ERROR:#DIV/0! Accept or Reject: Left Tail ERROR:#DIV/0! Accept or Reject: Left Tail ERROR:#DIV/0! Standard Error (StdError) =SQRT(PE*(1-PE)*(1/n1+1/n2)) ERROR:#DIV/0!
Accept or Reject: Right Tail ERROR:#DIV/0! Accept or Reject: Right Tail ERROR:#DIV/0! Accept or Reject: Right Tail ERROR:#DIV/0! Accept or Reject: Right Tail ERROR:#DIV/0! Test Statistic Z-stat =(Point-Hypo)/StdError ERROR:#DIV/0!
Accept or Reject: Two Tail ERROR:#DIV/0! Accept or Reject: Two Tail ERROR:#DIV/0! Accept or Reject: Two Tail ERROR:#DIV/0! Accept or Reject: Two Tail ERROR:#DIV/0! Accept or Reject: Left Tail ERROR:#DIV/0!
Accept or Reject: Right Tail ERROR:#DIV/0!
p-value (Lower Tail) =NORM.S.DIST(z,TRUE) ERROR:#DIV/0! p-value (Lower Tail) =NORM.S.DIST(z,TRUE) ERROR:#DIV/0! p-value (Lower Tail) =NORM.S.DIST(z,TRUE) ERROR:#DIV/0! p-value (Lower Tail) =NORM.S.DIST(z,TRUE) ERROR:#DIV/0! Accept or Reject: Two Tail ERROR:#DIV/0!
p-value (Upper Tail) =1-LowerTail ERROR:#DIV/0! p-value (Upper Tail) =1-LowerTail ERROR:#DIV/0! p-value (Upper Tail) =1-LowerTail ERROR:#DIV/0! p-value (Upper Tail) =1-LowerTail ERROR:#DIV/0!
p-value (Two Tail) =2*MIN(LowerTail,UpperTail) ERROR:#DIV/0! p-value (Two Tail) =2*MIN(LowerTail,UpperTail) ERROR:#DIV/0! p-value (Two Tail) =2*MIN(LowerTail,UpperTail) ERROR:#DIV/0! p-value (Two Tail) =2*MIN(LowerTail,UpperTail) ERROR:#DIV/0! p-value (Lower Tail) =NORM.S.DIST(Zstat,TRUE) ERROR:#DIV/0!
Accept or Reject p-value: Left Tail ERROR:#DIV/0! Accept or Reject p-value: Left Tail ERROR:#DIV/0! Accept or Reject p-value: Left Tail ERROR:#DIV/0! Accept or Reject p-value: Left Tail ERROR:#DIV/0! p-value (Upper Tail) =1-LowerTail ERROR:#DIV/0!
Accept or Reject p-value: Right Tail ERROR:#DIV/0! Accept or Reject p-value: Right Tail ERROR:#DIV/0! Accept or Reject p-value: Right Tail ERROR:#DIV/0! Accept or Reject p-value: Right Tail ERROR:#DIV/0! p-value (Two Tail) =2*MIN(LowerTail,UpperTail) ERROR:#DIV/0!
Accept or Reject p-value: Two Tail ERROR:#DIV/0! Accept or Reject p-value: Two Tail ERROR:#DIV/0! Accept or Reject p-value: Two Tail ERROR:#DIV/0! Accept or Reject p-value: Two Tail ERROR:#DIV/0! Accept or Reject p-value: Left Tail ERROR:#DIV/0!
Accept or Reject p-value: Right Tail ERROR:#DIV/0!
p-Lower Limit =pbar-CONFIDENCE.NORM(alpha,StdError,n) ERROR:#DIV/0! p-Lower Limit =pbar-CONFIDENCE.NORM(alpha,StdError,n) ERROR:#DIV/0! p-Lower Limit =pbar-CONFIDENCE.NORM(alpha,StdError,n) ERROR:#DIV/0! p-Lower Limit =pbar-CONFIDENCE.NORM(alpha,StdError,n) ERROR:#DIV/0! Accept or Reject p-value: Two Tail ERROR:#DIV/0!
p-Upper Limit =pbar+CONFIDENCE.NORM(alpha,StdError,n) ERROR:#DIV/0! p-Upper Limit =pbar+CONFIDENCE.NORM(alpha,StdError,n) ERROR:#DIV/0! p-Upper Limit =pbar+CONFIDENCE.NORM(alpha,StdError,n) ERROR:#DIV/0! p-Upper Limit =pbar+CONFIDENCE.NORM(alpha,StdError,n) ERROR:#DIV/0!
Based upon the count of cheaters, categorized into Business and Non-Business students, place the relevant numbers in the purple area of the table below and note the conclusion.
8. Test of Independence - Is cheating independent of College and athletic participation?
Comparing business and non-business students number of cheaters for athletes and non-athletes
Ho: all groups cheat at the same rate
Ha: there is a difference in cheating based upon College or Athletic participation
Independent Variable
Business Non-Business Calculations
Dependent variable Obs Exp Obs Exp Total ERROR:#DIV/0! ERROR:#DIV/0!
Athlete ERROR:#DIV/0! ERROR:#DIV/0! 0 ERROR:#DIV/0! ERROR:#DIV/0!
Non-Athlete ERROR:#DIV/0! ERROR:#DIV/0! 0
Total 0 0 0
Chi square Test statistic = ERROR:#DIV/0!
Level of signicance 0.05
# of rows 2
# of columns 2
df = 1 df = (rows - 1)(columns - 1)
p-factor = ERROR:#DIV/0!
Chi square critical 3.8415
Conclusion: ERROR:#DIV/0!