1. The overall predicted portion of Y score variability is measured by r squared. T or F
2. SS regression is the denominator in the F-ratio inference test for regression. T or F
3. SS residual is the numerator in the F-ratio inference test for regression. T or F
4. No correlation between two variables is numerically represented by -1.00. T or F
5. In regression the values of a and b are derived from sample data. T or F
6. Graph and discuss a positive correlation.
7. Graph and discuss a negative correlation.
8. List and discuss the components of the straight line equation for regression.
9. Explain how scatter away from the regression line is considered to be error.
G&W Chapter 15 questions
10. List and describe the components for the chi square formula.
11. Explain the difference between the chi square goodness of fit test and the test for independence.
12. Explain how degrees of freedom are calculated for the test for independence.
13. Explain how expected frequencies are calculated for the test for independence.
14. The phi coefficient is an effect size measure at the interval level of measurement. T or F
15. The formulas for the phi coefficient and for Cramer's V are very similar. T or F
16. Chi square can be used if the expected frequencies in a cell are less than 5. T or F
17. There is a form of chi square that can be used for repeated measures designs. T or F
S book questions
Chapter 8
18. Why is the chi square goodness of fit test the appropriate inference test for the basketball sales/ seasons example used in this chapter?
Chapter 9
19. Why is the chi square test of independence the appropriate inference test for the gender/ political affiliation example used in this chapter?
Chapter 10
20) This chapter introduces the concept of the ‘noise correction factor', in the context of the signal divided by noise. What is the noise correction factor?
Chapter 11
21. What is the purpose of the questions embedded in the statistical decision tree?
Lecture questions:
22. Each data point on a scatterplot indicates both an X value and a Y value. T or F
23. A positive correlation is graphically represented by a line of best fit that declines from upper left to lower right. T or F
24. A negative correlation is graphically represented by a line of best fit that rises from the lower left to the upper right. T or F
25. r is both a descriptive statistic and a statistical inference test. T or F
26. The Pearson's correlation coefficient is the correlation measure used for ordinal level data. T or F
27. In regression X is the criterion variable and Y is the predictor variable. T or F
28. Researchers usually do correlation analysis before regression analysis when analyzing data. T or F
29. Multiple regression has more than one criterion variable. T or F
30. The Spearman correlation coefficient can be used for ranked data. T or F
31. r and r squared are related. T or F
32. Chi square is the only inference test that does not have a table of critical numbers in the back of the book. T or F
33. Chi square can be used as an inference test for repeated measures designs. T or F
34. The chi square formula is used for each cell in a contingency table. T or F
35. The phi coefficient and the Cramer's V are effect size measures related to chi square. T or F
36. When testing for the strength of a relationship, if both variables are at the Nominal level the Pearson's correlation coefficient is the correct inference to use. T or F
37. In chi square degrees of freedom is based on sample size. T or F
38. Answering the questions in the statistical decision tree will ultimately lead you to the appropriate inference test to use to analyze your data. T or F
39. Explain the differences between a causal analysis, a predictive analysis and a correlational analysis.