Repeated measures designs reduce error variance as long as the scores are correlated.

Question 1Repeated measures designs reduce error variance as long as the scores are correlated.

  True

  False

 Question 2If there were 4 groups, how many possible pair-wise comparisons are there?

  3

  4

  5

  6

 Question 3In a two-group test, if a t is significant, the F will always be as well.

  True

  False

 Question 4Repeated measures designs increase the degrees of freedom involved in an analysis.

  True

  False

 Question 5What is a “confounding variable?”

  A variable which causes variance but is uncontrolled

  A variable which is mathematically controlled in an analysis

  A variable which is controlled but not measured

  A variable which correlates with other analyses

 Question 6Post-hoc tests identify the location of significant differences in an ANOVA.

  True

  False

Question 7The sum of squares, the standard deviation, the variance, and the range are all measures of data variability.

  True

  False

 Question 8The magnitude of any sum of square value reflects which of the following?

  The treatment effect

  The impact of the dependent variable

  The number of scores included

  The effect size

Question 9What measure of data variability did Fisher rely on for ANOVA?

  The F ratio

  The modified standard score

  The squared difference between particular values and the relevant mean

  The standard error of the difference between multiple groups

 Question 10Besides the tedium involved in performing all possible comparisons, what is the problem in conducting all possible t-test with multiple groups?

  Mounting alpha error

  Mounting beta error

  Locating significance

  Determining the effect size

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