If other factors are held constant, which of the following sets of data is most likely to produce a significant value for the repeated-measures t statistic?
n = 15 and SS = 10 for the difference scores |
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n = 15 and SS = 100 for the difference scores |
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n = 30 and SS = 10 for the difference scores |
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n = 30 and SS = 100 for the difference scores |
If other factors are held constant, which of the following sets of data is most likely to produce...
25 por QUESTION 4 Assuming that other factors are held constant, which of the following sets of data is most likely to produce a statistically significant value for the repeated measures t statistici n 15 and MD-2 On-15 and MD - 4 On - 30 and MD - 2 On - 30 and MD - 4 25 QUESTION 5 For which of the following situations would a repeated-measures research design be appropriate? comparing mathematical skills for girls versus boys at...
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Assuming that other factors are held constant, which of the following would tend to increase the likelihood of rejecting the null hypothesis? Decrease the sample size Increase the sample mean difference Increase the sample variance None of the other 3 options would increase the likelihood Which of the following is the correct null hypothesis for a repeated-measures t test? MD 0 M1 M2 One sample of n=8 scores has a variance of s 6 and a second...
answer all please
In an analysis of variance, the MS between and MS within represent the means of the squared variability between and within conditions. True • False QUESTION 14 If an analysis of variance produces SS between 30 and MS between 10, then the ANOVA is comparing three treatment conditions. True False QUESTION 15 Compared to an independent measures design a repeated measures study is more likely to find a statistically significant effect because it reduces the contribution of...
If other factors are held constant, explain how each of the following influences the value of the independent-measures t test? a. Increasing the number of people in each sample b. Increasing the size of variance for each sample c. Increasing the difference between the two sample means
Which set of sample characteristics is most likely to produce a larger t value for the independent-measures t statistic? a large mean difference and large sample variances a small mean difference and large sample variances a small mean difference and small sample variances Ca large mean difference and small sample variances
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Which of the following sets of sample data would produce the largest value for an independent-measures t statistic. Assume that n = 10 for all samples. Note: You should not need to do any serious calculations to answer this question. First sample: M 30 and SS 10, Second Sample: M 35 and SS 10 ● First sample : M = 30 and SS = 50, Second Sample: M = 35 and SS = 50 O First sample:...
24. Assuming that other factors are held constant, which of the following would tend to increase the likelihood of rejecting the null hypothesis? a. Decrease the sample size b. Increase the sample mean difference c. Increase the sample variance d. None of the other 3 options would increase the likelihood
er Preview we described a study Chants had more academic problems showing that students ights with less than average sleep wgtnits with more than average sleep Huynh,& Fuligni, 2013). Suppose Gillen-O'Neel her is attempting to replicate this stu researche! ple of n = 8 college freshmen. Each rds the amount of study time and amount each night and reports the number of problems each day. The following data show the results from the study Number of Academic Problems Following NightsFollowing...
please answer all of the following much appreciated!!
Question 8 Given the following 2 sets of data, what would the degrees of freedom be for an independent measures t-test? 12, 4, 9, 0, 1,5 2, 4, 8, 16,3 Question 9 4 points Save Answer Shannon Louise wants to see if dunking your face in cold water before a test causes a difference in test scores. She samples two groups, where one group will dunk their face into water before beginning...
For either independent-measures or repeated-measures designs comparing two treatments, the mean difference can be evaluated with either at test or an ANOVA. The two tests are related by the equation F=12. The following data are from a repeated-measures study: Person Difference Scores 3 I 4 2 3 7 M = 4.00 T = 16 SS = 14 Treatment II 7 11 6 10 M 8.50 T-34 SS = 17 3 3 Mo 4.50 SS = 27.00 Use a repeated-measures t...