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.
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Write My Essay For MeIndependent 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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