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Hypothesis Testing Assignment The goal of this assignment is to formulate reasonable hypotheses based on available data and then test these hypotheses in E

Hypothesis Testing Assignment The goal of this assignment is to formulate reasonable hypotheses based on available data and then test these hypotheses in E

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Hypothesis Testing Assignment The goal of this assignment is to formulate reasonable hypotheses based on available data and then test these hypotheses in Excel. You will formulate one hypothesis that can be tested with an independent samples t-test and one hypothesis that can be tested with a chi-square test of independence. The data represents results from a survey with households with families. The data file is included in the attached file. 
Instructions
For this assignment you will formulate two hypotheses based on the variables includes in the attached dataset, and provide an example of a marketing consequence (for a particular company or a group of companies) if you were to find support for your alternative hypotheses. In the next step, you will conduct hypotheses tests with the available sample data, and finally, you will interpret the results from your tests. Below I have provided step-by-step instructions.

Read chapter 11: The Chi-square distribution, in https://openstax.org/books/introductory-business-statistics/pages/11-introduction
This is another good description of the chi-square test: https://statisticsbyjim.com/hypothesis-testing/chi-square-test-independence-example/
This video provides step-by-step instructions for how to conduct a Chi-square test In Excel: https://www.youtube.com/watch?v=Ki5S9kmN2hI
This is a description of how to use the pivot table function in Excel to create the contingency (cross-tab) table you need for the Chi-square test: https://www.statology.org/contingency-table-excel/ Instructions

Instructions
For this assignment, you will formulate two hypotheses based on the variables included in the attached dataset and provide an example of a marketing consequence (for a particular company or a group of companies) for your alternative hypotheses. In the next step, you will conduct hypothesis tests with the available sample data, and finally you will interpret the results from your tests. Below I have provided step-by-step instructions.

Independent samples t-test
1. Use a copy of this file for your work and add tabs for your analysis. Start by saving a copy with your name in the file name.
2. Review the variables in the dataset and select one grouping (independent) variable and one dependent (outcome) for which you think it is reasonable to argue that the grouping variable affects the outcome variable. In other words, you think there will be a difference in the means for the dependent variable between the two groups.
3. Write an informal hypothesis that explains why this difference seems reasonable.
4. Explain why the hypothesis could be interesting to a company from a marketing standpoint.
5. Write a formal null and alternative hypothesis.
6. Make sure to add the data analysis package to your Excel if you haven’t done that previously for other classes (reach out for help if you don’t know how to do that).
7. Instructions for how to complete a t-test in Excel is available in the week 13 folder and in the assignment folder. I recommend selecting the option of getting the results on a separate worksheet ply/tab.
8. Interpret the t-test test statistic generated through Excel (2-3 sentences will be sufficient).

Chi-square test of independence: two categorical variables
1. Review the variables in the dataset and select two categorical variables that you think could be related, that is, it is reasonable to assume that the values on one of the variables will depend on the values of the other variable.
2. Write an informal hypothesis that describes what relationship between the variables you think is reasonable.
3. Explain why the hypothesis could be interesting to a company from a marketing standpoint.
4. Write a formal null and alternative hypothesis.
5. Use the pivot table function to create a cross-tab (contingency table) for your observed values.
6. Create a table for, and calculate, expected values.
7. Use the test option for chi-square under formulas/more functions.
8. Interpret the result generated through Excel (2-3 sentences will be sufficient).
9. The Chi-square test will be covered in class in week 14.

Data

Household No. of children at home Oldest child younger than 6 y. Pet owner Interest in meal kit services Target Circle member Average Grocery Bill / month Hours spent driving to/from kids’ activities/week 1st child after 35 (mother)

1 3 YES NO Yes, very interested NO 1092 3.75 yes

2 3 YES YES Yes, somewhat interested YES 816 3.7 yes

3 3 YES NO Yes, very interested NO 1137 3.6 no

4 3 YES YES Yes, very interested YES 843 3.5 yes

5 3 YES YES Yes, very interested YES 843 3.5 no

6 3 YES NO Yes, very interested NO 1176 3.3 yes

7 3 YES YES Yes, very interested NO 837 3.25 yes

8 2 YES YES Yes, somewhat interested NO 1048 1.4 yes

9 2 YES NO Yes, somewhat interested YES 690 3.2 no

10 3 YES YES Yes, very interested YES 816 3.2 yes

11 2 YES NO Yes, somewhat interested YES 638 3.15 yes

12 2 YES YES Yes, somewhat interested NO 766 3.15 yes

13 3 YES YES Yes, very interested NO 837 3.15 no

14 2 YES NO Yes, very interested YES 778 3.1 no

15 2 YES NO Yes, somewhat interested YES 778 3.1 yes

16 3 NO YES Yes, very interested NO 1005 3.1 no

17 2 YES NO Yes, somewhat interested YES 696 3.05 yes

18 2 YES NO Yes, somewhat interested YES 776 2.25 no

19 2 YES YES Yes, very interested NO 1048 3.05 yes

20 3 NO NO Yes, very interested YES 1050 3.05 no

21 2 YES NO Yes, very interested YES 776 2.95 yes

22 2 NO NO No, not interested NO 776 2.9 yes

23 2 NO YES No, not interested NO 798 2.85 no

24 1 NO NO No, not interested NO 413 2.8 yes

25 2 NO NO Yes, very interested NO 540 2.8 no

26 2 YES YES Yes, somewhat interested YES 542 2.8 yes

27 3 NO YES No, not interested NO 930 2.6 no

28 1 NO NO No, not interested YES 293 2.5 no

29 3 NO NO Yes, very interested NO 813 2.45 no

30 3 NO NO Yes, somewhat interested YES 1020 2.45 no

31 3 NO NO Yes, somewhat interested NO 1191 2.45 yes

32 2 NO NO No, not interested NO 738 2.4 no

33 3 NO YES No, not interested YES 1050 2.4 yes

34 3 NO NO Yes, somewhat interested NO 813 2.35 no

35 3 NO NO Yes, somewhat interested NO 900 2.35 yes

36 1 YES YES No, not interested YES 314 2.3 no

37 1 YES YES No, not interested NO 560 2.3 yes

38 1 YES YES Yes, very interested YES 279 2.25 no

39 2 NO YES No, not interested NO 660 2.25 no

40 3 NO YES Yes, somewhat interested NO 1107 2.25 no

41 1 YES NO No, not interested NO 392 2.2 no

42 3 NO YES Yes, somewhat interested NO 1010 2.2 yes

43 1 NO NO No, not interested NO 332 2.15 yes

44 1 YES NO No, not interested YES 356 2.15 yes

45 3 NO YES Yes, somewhat interested NO 930 2.15 no

46 3 NO YES Yes, very interested YES 1050 3.2 yes

47 1 YES YES Yes, somewhat interested YES 273 2.1 no

48 2 NO YES Yes, somewhat interested NO 798 3.5 yes

49 2 NO NO Yes, somewhat interested NO 910 2.1 no

50 2 NO YES Yes, somewhat interested YES 1146 1.95 yes

51 1 YES NO Yes, somewhat interested YES 334 1.9 yes

52 1 NO YES No, not interested NO 650 1.8 no

54 2 NO YES Yes, somewhat interested NO 704 2.35 no

54 2 YES YES Yes, somewhat interested YES 720 1.8 no

55 1 NO NO No, not interested NO 776 1.8 yes

56 1 NO NO Yes, somewhat interested YES 365 1.7 yes

57 2 YES NO Yes, somewhat interested YES 536 1.2 no

58 1 NO YES No, not interested YES 361 1.5 no

59 1 NO NO No, not interested NO 276 1.3 no

60 1 NO NO Yes, somewhat interested YES 316 4 no

Please note that you can sort the data based on any of the variables. You will need to sort your data based on your independent (grouping) variable in order to conduct your independent samples t-test analysis.

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