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PSY101 Introduction to Psychology B

Question:

1.) F-ratios are always greater than or equal to zero

2.) A research report presents the results of an independent-measures ANOVA as follows: F(3, 28) = 5.36, p

3.) SSbetween measures the size of the mean differences from one treatment to another

4.) A new laundry detergent is supposed to be equally superior to the leading brand in both hot and cold water. If the new detergent works as predicted, then there should be an interaction between the brand of detergent and the temperature of the water

5.) Post tests are only needed if H0 is rejected in an ANOVA comparing more than two treatments

6.) For an independent-measures ANOVA comparing four treatment conditions, dfbetween

7.) One concern for a repeated-measures study is that a participant’s score in one treatment may be influenced by practice or experience gained in a previous treatment

8.) For a repeated-measures design, the differences between treatments may be caused by a treatment effect or by sampling error (random factors), but they cannot be caused by individual difference

9.) For an independent-measures t statistic, you typically must compute the pooled variance before calculating the estimated standard error

10.) For the repeated-measures analysis, the F-ratio, on average, is expected to be zero when H0 is true

11.) The estimated standard error for the independent-measures t statistic provides a measure of how much difference should exist, on average, between two sample means when the null hypothesis is true

12.) A research study compares the mean weight for a sample of n = 36 participants before they begin a 6-week diet and their mean weight at the end of the diet. This is an example of an independent-measures design

13.) Whenever a two-factor experiment results in a significant interaction, you should be cautious about interpreting the main effects because an interaction can distort, conceal, or exaggerate the main effects of the individual factors

14.) An F-ratio near 1.00 is an indication that the null hypothesis is likely to be true

15.) If all of the participants in a repeated-measures study show roughly the same 10-point difference between treatments, then the data are likely to produce a significant value for the t statistic

16.) Because the repeated-measures ANOVA removes variance caused by individual differences, it usually is more likely to detect a treatment effect than the independent-measures ANOVA is

17.) If other factors are held constant, the larger the difference between the two sample means is, the greater the likelihood that the independent-measures t test will find a significant difference

18.) A two-factor study compares three different treatment conditions for males (factor 1) and females (factor 2). In this study, the main effect for gender is determined by the overall mean score for the males (averaged over the three treatments) and the corresponding overall mean score for the females

19.) The larger the differences among the sample means, the larger the numerator of the F-ratio will be

20.) The results from an independent-measures t hypothesis test are reported as “t(14) = 2.10, p > .05, two tailed.” For this test, the null hypothesis was rejected

21.) The homogeneity of variance assumption states that the two population variances are equal

22.) In a repeated measures study, the null hypothesis says that the mean for the sample of difference scores is equal to zero

23.) For an independent-measures two-factor analysis of variance, all of the F-ratios use the same denominator

24.) Post tests such as Scheffé are not necessary for an analysis of variance comparing only two treatment conditions

25.) In analysis of variance, large sample variances reduce the likelihood of rejecting the null hypothesis

26.) One advantage of a repeated-measures design is that it typically requires fewer participants than an independent-measures design

27.) An ANOVA is used to determine whether significant difference exists, and post tests are used to determine exactly which treatment means are significantly different

28.) For an ANOVA, when the null hypothesis is true, the F-ratio is balanced so that the numerator and the denominator are both measuring the same sources of variance

29.) The distribution of F-ratios is negatively skewed

30.) In the second stage of the repeated-measures ANOVA, individual differences are removed from the denominator of the F-ratio

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