1. Use the data in Chapter 14 Data Set 3 to answer the questions below. Do this one manually or use SPSS.
a. Compute the correlation between income and level of education.
b. Test for the significance of the correlation.
C. What argument can you make to support the conclusion that “lower levels of education cause low income”?
Discuss the general idea that just because two things are correlated, it does not mean that one causes the other. Provide an example (other than ice cream and crime!).
2. Betsy is interested in predicting how many 75-year-olds will develop Alzheimer’s disease and is using predictors level of education and general physical health graded on a scale from 1 to 10. But she is interested in using other predictor variables as well. Answer the following questions.
a. What criteria should she use in the selection of other predictors?
b. Name two other predictors that you think might be related to the development of Alzheimer’s disease.
c. With the four predictor variables (level of education and general physical health, and the two new ones that you named), draw out what the model of the regression equation would look like.
3. Go to the library and locate three different examples of where linear regression was used in a research study in your area of interest. It’s OK if the study contains more than one predictor variable. Answer the following questions for each study.
Heathcote, J.A. (1995) Why do old men have big ears? British Medical Journal 311, 1668
Taylor CE, Jones H., Blood pressure status and post-exercise hypotension: an example of spurious correlation in hypertension research?
Mehrad J., Goltaji M. Correlation between Journal self-citation and Impact factor in ISC’s PJCR Agriculture and Veterinary Science Journals during 2001-2007
a. What is one independent variable? What is the dependent variable?
b. If there is more than one independent variable, what argument does the researcher make that these variables are independent from one another?
c. Which of the three studies seems to present the least convincing evidence that the dependent variable is predicted by the independent variable, and why?