Question 10 1 pts What is the biggest advantage for using the paired-samples t-test over the independent-samples t-test? Paired-samples t-test has more statistical assumptions. Paired-samples t-test has a more practical study design. Paired-samples t-test has less power to reject the null hypothesis. Paired-samples t-test has more power to reject the null hypothesis. Question 11 1 pts The F-statistic from an ANOVA is essentially a ratio of ________ variance.
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Which of the following is the null hypothesis for an independent sample t-test? In an independent-measures study, the null hypothesis states that there is no significant difference between the means of the two groups being compared. Which of the following is the standard error of an independent sample t-test? In an independent-measures experiment, a sample with n=16 is compared to a second sample. The statistic from this experiment will have degrees of freedom equal to the sum of the degrees of freedom for each sample. One sample has n=10 and SS=50, and the second sample has... What is the pooled variance for the two samples? For which of the following situations would a repeated-measures design be appropriate?
Madhur L.
Why is the related samples t-test more powerful than the independent samples t-test? There are often more people involved in the related samples t-test, so N is bigger. By relating the samples, one is eliminating a lot of the sources of error, thus reducing the standard error. There are fewer degrees of freedom in the related samples t-test. The related samples t-test is always conducted as a directional or one-tailed test. Critical values are always smaller and easier to get beyond to reject the null hypothesis in related samples t-test.
Adi S.
One of the primary advantages of a repeated-measures design, compared to an independent-measures design, is that it reduces the overall variability by removing variance caused by individual differences. The following data are from a research study comparing three treatment conditions. Treatment A B C P 6 9 12 27 N = 18 8 8 8 24 G = 108 5 7 9 21 Sum(X²) = 800 0 4 8 12 2 3 4 9 3 5 7 15 M = 4 M = 6 M = 8 T = 24 T = 36 T = 48 SS = 42 SS = 28 SS = 34 a) Assume that the data are from an independent-measures study using three separate samples, each with n = 6 participants. Ignore the column of P totals and use an independent-measures ANOVA with alpha = .05 to test the significance of the mean differences. b) Now assume that the data are from a repeated-measures study using the same sample of n = 6 participants in all three treatment conditions. Use a repeated-measures ANOVA with alpha = .05 to test the significance of the mean differences. c) Explain why the two analyses lead to different conclusions.
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