BUSINESS 307 

Lab Assignment # 3

Analysis of Variance and Two-Sample Tests

Total Marks: 45 Weight 4%

Due: Wednesday, March 24, 2021

Please submit this assignment according to the instructions on the top of Assignment #1.

For the questions below, use the most efficient Excel formula or procedure to find your answer. Calculations by hand (or calculator) should only be used to check your answers. Show relevant Excel output and/or formulas and results. For this assignment you will be using the BUS 306 Survey Data.xlsx file from BlackBoard. Immediately save this file to your H: drive or memory stick. For purposes of this assignment consider these to be sample data.

Please complete the following tasks:

Is there a significant difference between variances of gender and hours per week spent being physical active? [Hint: remove any blanks from each column, remembering to sort the columns together.] Use an F test (on pages A-2 and A-3 of your Class Notes book). (You are advised NOT to use the Two-sample F-test in the Analysis Toolpak. Do the problem using simple formulas and functions.) Use an alpha of 10%. Show your hypotheses, calculation of F* using Excel, and either the critical F value(s) or p-value, calculated by Excel, and decision. Describe the difference if one exists. [9]

In this task you will use ANOVA to analyze the relationship between the major that the student is in (or planning to go into) and “How many hours of out-of-class study PER WEEK, FOR A FIVE COURSE WORKLOAD, do you think should be expected of you?” Eliminate any blanks from both variables. Also, we will only keep the top three majors (the ones with the highest counts). Eliminate the other majors. Use ANOVA – single factor in Excel’s Data Analysis ToolPak to test whether there is a relationship between the two variables. Use an alpha of 10% Show your hypotheses, ANOVA output, and decision – referring to numbers in the ANOVA output. If there is a relationship, describe it in non-statistical language, with a visual analysis of the means. Then, use Excel to create formulas for a Multiple Means (Fishers) comparison for the two means that differ the most. Show the Excel formulas that are used to do the comparison, using constants (rather than cell references) from the ANOVA output as well as the Excel T… function. (Do not use the output from the ANOVA Template.xlsx file.) How does the Fishers test support your conclusion? (Note: Consider the categories of the three majors to be your treatments.) [11]

Redo the question above (major vs. expected hours of studying) using a Kruskal-Wallis test (with an alpha of 10%). Use the ANOVA Template.xlsx found in the Supplementary Files folder to do your calculations. Show your modified hypotheses for the K-W test, results from the output and decision. Do your results match those from the question above? Why or why not? (Support with appropriate output from necessary tests to test the ANOVA conditions. Do not include a test if it is not necessary to test the ANOVA conditions.) Describe the relationship, if one exists, in words that a non-statistician would understand. (Note: it is not necessary to do a Fishers’ comparison.) [9]

Test to see if there is a relationship between gender and how stressed students feel about going to school. Eliminate any blanks for both variables. You will also need to recode your ratings where ‘Strongly Disagree’=1, ‘Disagree’=2, etc. Show your hypotheses (with appropriate subscripts), appropriate output, and your decision based on the output. Describe the difference, if one exists. Use an alpha of 5%. [Hint: Use ANOVA Template.xlsx.] [7]

Use one of the two-sample hypothesis tests (Unit T) to see if there are significant differences between mean hours per week spent being physical active for females compared to males. Eliminate any rows that don’t have values for both variables. Show your hypotheses, appropriate output for this two-sample hypothesis test from the Data Analysis Toolpak, p-value from the output, and decision. Describe the difference, if one exists. Use an alpha of 1%. [9]