Chapter 11 -- Measuring Item Interactions

1			All measures of association between pairs of variables require that one be identified as dependent and the other as independent.
			A)	TRUE
			B)	FALSE
2			Merely knowing the name of a variable or what it represents doesn't necessarily indicate whether it's a dependent or independent variable for a given analysis.
			A)	TRUE
			B)	FALSE
3			A relationship between two variables can be significant without being important.
			A)	TRUE
			B)	FALSE
4			The significance probability answers the question, "What's the chance this much of a relationship would result from sampling error if it didn't exist in the population."
			A)	TRUE
			B)	FALSE
5			Cross-tabulation requires the dependent variable to define the rows and the independent variable to define the columns.
			A)	TRUE
			B)	FALSE
6			With Analysis of Variance, the number of cases in each group has to be the same.
			A)	TRUE
			B)	FALSE
7			With Analysis of Variance, the smaller the F-ratio probability, the more significant the result is likely to be.
			A)	TRUE
			B)	FALSE
8			Correlation analysis does NOT require specification of a dependent and independent variable.
			A)	TRUE
			B)	FALSE
9			With correlation, the percentage of shared variance is revealed by the square root of the correlation coefficient.
			A)	TRUE
			B)	FALSE
10			Regression analysis requires the dependent variable to define the vertical axis of a plot and the independent variable to define the horizontal axis.
			A)	TRUE
			B)	FALSE