Data Set 18 “Speed Dating” in Appendix B includes data from 199 dates. Due to the large size of this data set, the data are available at www.TriolaStats.com. Download the data set and proceed to investigate correlations between pairs of variables using the data in the 5th, 7th, and 9th columns, which are all based on responses by females. Use the “like” measures by females as the y variable in each case.

1. Is there a correlation between “like” measures and attractiveness measures?
2. Is there a correlation between “like” measures and attribute measures?
3. Is there a correlation between attractiveness measures and attribute measures?
4. If Section 10-5 (Multiple Regression) was covered, investigate correlation and regression using the “like” measures as the y variable and use the attractiveness measures and attribute measures as the other two x variables.
5. Repeat the above using the 6th, 8th, and 10th columns, which are all based on responses by males.
6. Based on the results, what do you conclude? Write a brief report and include appropriate computer results.

Data Set 18: Speed Dating 

Data are from 199 dates (first five rows shown here). DEC BY FEM is decision (1 = yes) of female to date again, AGE FEM is age of female, LIKE BY FEM is “like” rating by female of male (scale of 1-10), ATTRACT BY FEM is “attractive” rating by female of male (scale of 1-10), ATTRIB BY FEM is sum of ratings of five attributes (sincerity, intelligence, fun, ambitious, shared interests) by female of male. Data for males use corresponding descriptors. Higher scale ratings correspond to more positive impressions.

Based on replication data from Data Analysis Using Regression and Multilevel>Hierarchical Models, by Andrew Gelman and Jennifer Hill, Cambridge University Press.