This is a set of data from 100 people who completed a scale designed to measure optimism.
Question:
This is a set of data from 100 people who completed a scale designed to measure optimism. The first item (column 1) is "Treatment" and refers to 50 people who were given no training in how to be optimistic (a control group - labeled with a zero) and 50 people who went through an optimism training program (labeled with a one). The next 7 columns each represent the 7 questions from the optimism scale.
The items are:
- In uncertain times, I usually expect the best
- It's easy for me to relax
- I'm always optimistic about my future
- I enjoy my friends a lot
- My life doesn't suck too much
- I don't get upset too easily
- Overall, I expect more good things to happen to me than bad
The participants rated each question on a -3 (definitely not) to a +3 (definitely) scale. The researcher believes that their "optimism program" helps people become more optimistic. The null hypothesis is thus that no difference exists between the treatment and control groups.
For this assignment I want you to answer the following questions:
- Are any of the seven optimism-scale questions "bad"? Tell me which one, and tell me how you know it's bad. (Hint: there is 1 bad question). - 4 points
A couple more hints...
After reading the items you should see that you don't need to reverse code anything.The data is already "clean"
table.
| Treatment | Opt1 | Opt2 | Opt3 | Opt4 | Opt5 | Opt6 | Opt7 |
| 0 | -2 | -3 | -3 | 3 | 1 | -3 | -2 |
| 0 | -2 | -3 | -2 | 3 | -3 | -3 | 0 |
| 0 | -3 | -3 | -3 | 3 | -1 | 0 | 0 |
| 0 | -2 | -2 | -2 | 3 | -1 | -3 | 1 |
| 0 | 2 | -2 | -3 | -2 | -3 | 0 | 1 |
| 0 | 0 | -2 | -1 | 1 | 3 | 0 | -1 |
| 0 | -1 | -2 | -1 | 3 | 0 | -1 | -1 |
| 0 | 0 | -1 | 0 | 1 | 1 | -1 | -1 |
| 0 | -1 | -1 | -1 | 3 | 1 | -2 | 1 |
| 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
| 0 | -1 | -2 | 2 | 3 | 0 | -1 | -1 |
| 0 | -1 | 2 | -1 | 2 | 1 | -1 | -1 |
| 0 | -1 | -1 | 1 | 3 | 3 | -2 | 1 |
| 0 | 1 | -1 | -1 | 2 | 2 | -3 | 3 |
| 0 | 0 | -3 | 2 | 3 | 1 | -3 | 3 |
| 0 | -1 | 1 | -1 | 3 | -3 | -2 | 2 |
| 0 | 0 | 0 | 1 | 1 | 0 | -1 | 1 |
| 0 | -1 | 2 | -2 | 3 | 1 | 0 | 1 |
| 0 | -1 | 1 | -1 | 3 | 1 | 1 | 0 |
| 0 | 1 | -2 | 1 | 1 | 0 | 1 | 1 |
| 0 | 1 | -1 | 1 | 3 | 1 | -1 | 0 |
| 0 | -3 | 3 | -1 | 3 | 1 | 3 | -2 |
| 0 | 1 | -1 | 1 | 3 | 2 | -1 | 1 |
| 0 | -1 | -1 | 1 | 3 | 2 | 1 | 2 |
| 0 | 1 | -2 | 2 | 1 | -2 | 1 | 2 |
| 0 | 1 | 0 | 1 | 2 | -1 | 1 | 0 |
| 0 | 1 | -1 | 2 | 3 | 1 | 2 | -1 |
| 0 | 2 | 1 | 2 | 1 | 2 | -1 | 1 |
| 0 | 1 | 2 | 2 | 3 | 1 | 1 | -2 |
| 0 | 1 | 2 | 2 | 3 | 3 | -2 | 1 |
| 0 | 2 | 1 | 1 | 3 | 1 | -1 | 1 |
| 0 | 2 | 1 | 1 | 3 | 3 | -2 | 2 |
| 0 | 1 | -1 | 2 | 3 | 2 | 1 | 1 |
| 0 | 1 | 1 | 2 | 3 | 1 | -2 | 3 |
| 0 | 1 | 1 | 2 | 3 | 2 | 0 | 2 |
| 0 | 1 | 1 | 2 | 1 | 0 | 2 | 2 |
| 0 | 1 | 2 | 1 | 2 | 3 | 2 | 1 |
| 0 | 1 | 3 | 1 | 3 | 3 | -1 | 3 |
| 0 | 1 | 2 | 1 | 3 | 1 | 1 | 2 |
| 0 | 3 | 1 | 2 | 3 | -1 | -1 | 2 |
| 0 | 0 | 3 | 1 | 3 | 1 | 1 | 3 |
| 0 | 1 | 2 | 2 | 3 | -1 | 1 | 2 |
| 0 | 2 | 2 | 2 | 3 | -1 | 0 | 2 |
| 0 | 2 | 1 | 3 | 3 | 3 | 1 | 3 |
| 0 | 2 | 2 | 3 | 3 | 0 | 2 | 3 |
| 0 | 0 | 3 | 3 | 3 | 0 | 3 | 3 |
| 0 | 2 | 2 | 3 | 3 | 1 | 2 | 3 |
| 0 | 3 | 2 | 3 | 3 | 3 | 2 | 3 |
| 0 | 3 | 3 | 3 | 3 | 3 | 2 | 3 |
| 0 | 2 | 3 | 3 | 3 | 2 | 3 | 3 |
| 1 | -3 | -3 | -3 | 1 | 2 | -3 | -3 |
| 1 | -3 | -3 | -2 | 2 | 1 | -3 | -3 |
| 1 | -2 | -2 | -2 | -1 | 3 | -2 | -1 |
| 1 | -2 | -2 | -3 | 1 | 1 | -2 | -1 |
| 1 | -3 | -2 | -3 | 3 | 2 | -1 | -1 |
| 1 | -1 | -1 | -1 | 1 | 3 | -3 | -1 |
| 1 | -1 | -1 | -2 | 3 | 3 | -3 | -2 |
| 1 | -1 | -2 | -2 | 3 | 1 | -1 | -2 |
| 1 | 1 | -1 | -1 | 0 | -2 | -1 | -2 |
| 1 | 0 | -1 | -1 | -2 | 1 | 2 | -2 |
| 1 | -3 | 1 | -2 | 3 | -2 | -2 | -1 |
| 1 | -1 | -3 | -1 | 3 | -2 | -3 | 1 |
| 1 | 0 | -2 | -1 | 3 | -1 | -3 | 0 |
| 1 | -1 | -2 | 1 | 3 | 3 | -3 | -1 |
| 1 | -2 | 3 | -2 | 2 | -2 | -3 | 0 |
| 1 | -1 | -1 | -1 | 1 | 3 | -1 | 1 |
| 1 | -2 | 2 | -1 | 2 | 3 | -2 | -1 |
| 1 | -1 | -1 | -1 | 2 | 3 | -1 | 0 |
| 1 | 1 | -3 | 2 | 3 | -1 | -3 | -1 |
| 1 | 1 | -1 | -2 | 3 | 0 | -2 | 0 |
| 1 | -1 | -1 | -1 | 3 | -3 | -1 | 1 |
| 1 | 0 | 1 | -1 | 2 | 3 | -1 | -1 |
| 1 | 1 | 2 | -1 | -1 | 3 | -3 | 2 |
| 1 | 0 | 0 | 0 | 0 | 2 | 0 | 0 |
| 1 | -1 | 1 | -1 | 3 | -3 | -2 | 0 |
| 1 | -1 | 1 | -1 | 2 | -2 | -1 | 0 |
| 1 | 1 | -1 | -1 | 1 | 3 | 2 | -1 |
| 1 | -2 | -2 | 1 | 3 | 2 | 1 | 0 |
| 1 | 2 | -1 | 0 | 2 | -1 | 0 | -1 |
| 1 | 0 | 1 | -3 | 3 | 2 | 1 | 0 |
| 1 | -1 | 1 | -1 | 3 | 2 | -1 | 1 |
| 1 | 1 | -1 | 1 | 1 | -1 | 1 | -1 |
| 1 | -1 | 1 | -1 | 3 | 3 | -1 | 1 |
| 1 | -1 | 1 | 0 | 3 | -1 | -1 | 1 |
| 1 | 1 | -2 | 1 | 3 | 3 | -1 | 1 |
| 1 | 2 | -2 | 1 | 3 | 1 | -1 | 1 |
| 1 | -2 | 2 | 1 | 2 | -3 | 2 | 0 |
| 1 | -2 | -2 | 3 | 3 | -1 | 0 | 3 |
| 1 | 0 | 0 | 2 | 1 | 2 | 2 | 1 |
| 1 | 1 | -1 | 2 | 3 | 1 | 1 | 1 |
| 1 | 1 | 1 | 1 | 3 | 2 | -1 | 2 |
| 1 | 2 | 0 | 2 | 3 | 2 | -1 | 2 |
| 1 | 1 | 1 | 1 | 3 | 1 | 2 | 1 |
| 1 | 1 | 2 | 3 | 3 | 3 | -1 | 2 |
| 1 | 2 | 1 | -2 | 3 | 2 | 3 | 3 |
| 1 | 0 | 1 | 2 | 3 | 1 | 2 | 3 |
| 1 | 2 | 2 | 3 | 3 | 0 | 3 | 1 |
| 1 | 3 | 3 | 2 | 3 | 2 | 3 | 1 |
| 1 | 3 | 2 | 3 | 3 | 1 | 2 | 3 |
| 1 | 3 | 3 | 3 | 3 | 2 | 3 | 3 |
| Ttest |
| 1.984467455 |
| 0.038632372 |
| 0.196551196 |
| Opt1 | 1 | ||||||
| Opt2 | 0.39225376 | 1 | |||||
| Opt3 | 0.653662029 | 0.406734984 | 1 | ||||
| Opt4 | 0.04044397 | 0.19906527 | 0.287403881 | 1 | |||
| Opt5 | 0.166314231 | 0.144322836 | 0.135551957 | 0.004724292 | 1 | ||
| Opt6 | 0.439531673 | 0.484617401 | 0.495220587 | 0.036002844 | 0.071705871 | 1 | |
| Opt7 | 0.547747345 | 0.459113496 | 0.599618063 | 0.299581166 | 0.067559957 | 0.324285819 | 1 |
Expert Answer:
