#5
| ID | Spending ($) | Duration (minutes) | Age | Gender (0=male, 1=female) | Travel (minutes) | Dietary Preference | Member? |
| 1 | 65 | 21 | 18 | 0 | 15 | Regular | Yes |
| 2 | 26 | 4 | 25 | 0 | 20 | Regular | No |
| 3 | 44 | 31 | 17 | 0 | 15 | Regular | No |
| 4 | 31 | 33 | 48 | 0 | 10 | Low-carb | No |
| 5 | 5 | 9 | 28 | 0 | 25 | Low-fat | Yes |
| 6 | 95 | 47 | 55 | 0 | 40 | Regular | No |
| 7 | 12 | 35 | 33 | 0 | 20 | Low-fat | Yes |
| 8 | 125 | 43 | 51 | 0 | 35 | Low-carb | No |
| 9 | 8 | 7 | 25 | 0 | 5 | Regular | Yes |
| 10 | 85 | 18 | 32 | 0 | 10 | Low-carb | No |
| 11 | 80 | 49 | 29 | 0 | 25 | Regular | No |
| 12 | 102 | 61 | 28 | 0 | 50 | Regular | No |
| 13 | 89 | 36 | 30 | 0 | 15 | Low-carb | No |
| 14 | 68 | 48 | 19 | 0 | 60 | Low-fat | No |
| 15 | 122 | 57 | 62 | 0 | 10 | Low-carb | No |
| 16 | 73 | 56 | 30 | 1 | 35 | Low-fat | Yes |
| 17 | 188 | 68 | 40 | 1 | 70 | Regular | Yes |
| 18 | 256 | 47 | 51 | 1 | 25 | Low-carb | No |
| 19 | 113 | 53 | 45 | 1 | 30 | Low-fat | Yes |
| 20 | 88 | 39 | 68 | 1 | 5 | Low-fat | Yes |
| 21 | 188 | 57 | 29 | 1 | 10 | Low-carb | Yes |
| 22 | 76 | 27 | 30 | 1 | 30 | Low-fat | No |
| 23 | 197 | 67 | 47 | 1 | 45 | Low-carb | Yes |
| 24 | 99 | 30 | 33 | 1 | 20 | Regular | Yes |
| 25 | 238 | 61 | 90 | 1 | 15 | Low-carb | No |
| 26 | 47 | 52 | 16 | 1 | 30 | Low-fat | Yes |
| 27 | 166 | 26 | 43 | 1 | 40 | Low-carb | Yes |
| 28 | 85 | 51 | 36 | 1 | 60 | Low-fat | Yes |
| 29 | 159 | 64 | 71 | 1 | 45 | Regular | Yes |
| 30 | 200 | 50 | 48 | 1 | 20 | Low-fat | No |
| Regular | Low-fat | Low-carb |
| 65 | 5 | 31 |
| 26 | 12 | 125 |
| 44 | 68 | 85 |
| 95 | 73 | 89 |
| 8 | 113 | 122 |
| 80 | 88 | 256 |
| 102 | 76 | 188 |
| 188 | 47 | 197 |
| 99 | 85 | 238 |
| 159 | 200 | 166 |
Bimble now wants to predict the amount of spending ($) from the duration of customers' stay (minutes) according to the sample data.
5-1 Run an appropriate regression model and report the coefficients below. (select from the dropdown)
Spending ($) = [ Select ] ["1.24", "2.38", "3.49", "4.16", "5.33"] + [ Select ] ["1.24", "2.38", "3.49", "4.16", "5.33"] Duration (minutes)
5-2 Approximately what percentage of the variation in spending can be explained by the duration? (select from the dropdown)
[ Select ] ["0", "10", "20", "30", "40", "50", "60", "70", "80", "90", "100"] %
5-3 Bimble spends 40 minutes shopping at Bumble’s store. What is her estimated amount of spending, approximately? (select from the dropdown)
$ [ Select ] ["0", "20", "40", "60", "80", "100", "120", "140", "160", "180", "200", "220", "240", "260", "280", "300"]
5-4 Complete the sentence below for the correct interpretation of the slope of the regression model. (select from the dropdown)
For every additional minute stayed in the store, the amount of spending would [ Select ] ["increase", "decrease"] by approximately $ [ Select ] ["0", "1", "2", "3", "4", "5"] .
5-5 Bimble finds the t-test results next to the slope value in the Excel regression output.
What is the p-value? (select from the dropdown)
[ Select ] ["less than 0.005", "between 0.005 and 0.01", "between 0.01 and 0.025", "between 0.025 and 0.05", "between 0.05 and 0.10", "between 0.10 and 0.90", "greater than 0.90"]
What is your conclusion at α = 0.05? (select from the dropdown)
[ Select ] ["There is no linear relationship between spending and duration in the population.", "There is a positive linear relationship between spending and duration in the population.", "There is a negative relationship between spending and duration in the population.", "There is a curvilinear relationship between spending and duration in the population.", "None of the above."]