7.2 Data sets
7.2.1 Teacher Ratings
Does an instructor’s prior reputation affect student ratings?
Before viewing the lecture, students were given a summary of the instructors’ prior teaching evaluations. There were two conditions: Charismatic instructor and Punitive instructor.
Then all subjects watched the same twenty-minute lecture given by the exact same lecturer. Following the lecture, subjects answered three questions about the leadership qualities of the lecturer. A summary rating score was computed and used as the variable “rating” here.
| Variable | Description |
|---|---|
| Condition | Represents the content of the description that the students were given about the professor (1 = charismatic, 2 = punitive) |
| Rating | How favorably the subjects rated the professor after hearing the lecture (higher ratings are more favorable) |
| Note: Student Evaluation of Teacher Performance by Louisa Coburn |
Questions
- What is the independent variable in this study?
- What is the standard deviation of the ratings in the charismatic-reputation condition? What is the standard deviation of the ratings in the punitive-reputation condition?
- Plot side-by-side box plots for the ratings by condition.
- In which of the two conditions are there outliers?
- Conduct an independent-samples t-test to examine the difference between the mean ratings of the charismatic-reputation condition and the punitive-reputation condition. Is the difference in mean ratings statistically significant? What can you conclude?
Adapted from here
7.2.2 Smiles and Leniency
Does smiling increase leniency? Are different types of smiles differentially effective?
There is evidence that smiling can attenuate judgments of possible wrongdoing. This phenomenon termed the “smile-leniency effect”. Research on the effects of smiling has shown that a smiling person is judged to be more pleasant, attractive, sincere, sociable, and competent than a non-smiling person
| Variable | Description |
|---|---|
| Smile | Values = 1 is false smile , 2 is felt smile, 3 is miserable smile, 4 is neutral control |
| Leniency | A measure of how lenient the judgments were. |
| Note: . |
Questions
- Create parallel boxplots of Leniency for the four conditions.
- Find the mean, median, standard deviation, and interquartile range of Leniency for each group
- Compare each mean to the neutral smile mean using independent-samples t-tests.
Adapted from here
7.2.3 Credit Card Expenditure
Does being self-employed affect credit card expenditure? Does owning a home affect that expenditure?
- The 13444 observations in the data set are based on credit card applications.
- Of the full sample, 10499 applications were approved and the next 12 months of spending and default behavior were observed. Spending is the average monthly expenditure in the 12 months after the account was initiated.
- Average monthly income and number of household dependents are among the demographic data in the application.
| Variable | Description |
|---|---|
| card | Factor. Was the application for a credit card accepted? |
| reports | Number of major derogatory reports. |
| age | Age in years plus twelfths of a year. |
| income | Yearly income (in USD 10,000). |
| share | Ratio of monthly credit card expenditure to yearly income. |
| expenditure | Average monthly credit card expenditure. |
| owner | Factor. Does the individual own their home? |
| selfemp | Factor. Is the individual self-employed? |
| dependents | Number of dependents. |
| months | Months living at current address. |
| majorcards | Number of major credit cards held. |
| active | Number of active credit accounts. |
| Note: Greene, W.H. (2003). Econometric Analysis, 5th edition. Upper Saddle River, NJ: Prentice Hall. |
Questions
- Describe the data set
- Plot side-by-side box plots for income and expenditure by owner
- Plot side-by-side box plots for income and expenditure by selfemp
- Are there outliers? Where?
- Conduct an independent-samples t-test to examine the difference between the mean income of the accepted applications and the non-accepted ones. Is the difference in mean income statistically significant? What can you conclude?
- Conduct an independent-samples t-test to examine the difference between the mean age of the accepted applications and the non-accepted ones. Is the difference in mean age statistically significant? What can you conclude?
- Conduct an independent-samples t-test to examine the difference between the mean expenditure of the accepted applications with 0 or 1 dependents and the others. Is the difference in mean expenditure statistically significant? What can you conclude?
Adapted from here
7.2.4 Economics Journal Subscription
Does being published by a scholarly society affect the price?
- Data on 180 economic journals, collected in particular for analyzing journal pricing.
| Variable | Description |
|---|---|
| title | Journal title |
| publisher | factor with publisher name. |
| society | factor. Is the journal published by a scholarly society? |
| price | Library subscription price. |
| pages | Number of pages. |
| charpp | Characters per page. |
| citations | Total number of citations |
| foundingyear | Year journal was founded. |
| subs | Number of library subscriptions. |
| field | factor with field description. |
| Note: Bergstrom, T. (2001). Free Labor for Costly Journals? Journal of Economic Perspectives, 15, 183–198. |
Questions
- Describe the data set
- Plot side-by-side box plots for price and pages by society
- Plot side-by-side box plots for price by field (General vs rest)
- Are there outliers? Where?
- Conduct an independent-samples t-test to examine the difference between the mean price of the Journals published by a scholarly society and the others. Is the difference in mean price statistically significant? What can you conclude?
- Conduct an independent-samples t-test to examine the difference between the mean price of the General journals and the rest of fields. Is the difference in mean price statistically significant? What can you conclude?
- Conduct an independent-samples t-test to examine the difference between the mean price of the Journals founded before 1973 and the Journal founded from 1973. Is the difference in mean price statistically significant? What can you conclude?
Adapted from here