1. Of the following four research questions, which one are appropriate for the chi-square test?
a.The difference between the average scores of two math classes.
b.The difference between the number of children who passed the math test in Class 1 and the number of children who passed the math test in class 2.
c. The number of cars that passed the CRASH Test this year versus last year.
d. The speed with which a soccer player can run 100 yards compared to the speed of a football player.
2. Use the data in Chapter 14 Data Set 2 to answer the questions below. Do the analysis manually or using SPSS. attachment: Chapter 14 Data Set 2
a. Compute the correlation between motivation and GPA.
b. Test for the significance of the correlation coefficient at the .05 level using a two-tailed test.
c. True or False? The more highly you are motivated, the more you will study. Which did you select and why.
3. Use the data in Chapter 14 Data Set 3 to answer the questions below. Do this one manually or use SPSS.attachment: Chapter 14 Data Set 3
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"?
4. 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!).
5. Betsy is interested in predicting how many 75-year-olds will develop Alzheimer's disease and is using a 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 names), draw out what the model of the regression equation would look like.
6. 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.
7. 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?
8. Here's where you can apply the information in one of this chapter's tips and get a chance to predict a Super Bowl winner! Joe Coach was curious to know if the average number of games won in a year predicts Super Bowl performance (win or lose). The X variable was the average number of games won during the past 10 seasons. The Y variable was whether the team ever won the Super Bowl during the past 10 season. Here are the data:
Average Number of Bowl? (1 = yes
Team Wins Over 10 Years and 0 = no)
Savannah Sharks 12 1
Pittsburgh Pelicans 11 0
Williamstown Warriors 15 0
Bennington Bruisers 12 1
Atlanta Angels 13 1
Trenton Terrors 16 0
Virginia Vipers 15 1
Charleston Crooners 9 0
Harrisburg Heathens 8 0
Eaton Energizers 12 1
a. How would you assess the usefulness of the average number of wins as a predictor of whether a team ever won a Super Bowl?
b. What's the advantage of being able to use a categorical variable (such as 1 or 0) as a dependent variable?
c. What other variables might you use to predict the dependent variable, and why would you choose them?
Attachment:- CHAPTER 14 Data Set 2.3.xlsx