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Hypothesis Testing, Cohen's d & Effect Size

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1. One sample has SS= 35 and the second sample has SS=45.
a) assume that n=6 for both, calculate the sample variance, and the pooled variance.
b) assume that n=6 for one and n=16 for the other, calculate the two sample variances and the pooled variance.

2. A sample of n=10 people receive medication with pain tolerance and n=10 for people who received a placebo. The score for the placebo group produce a mean of M=38 with SS=150
a) if the score for the medication group have a mean of M=42 with SS= 210, are the data sufficient to conclude that the medication has a significant effect? Use a two tailed test with α= .05
b) the medication group averaged 4 points higher than the controlled group.If the effect was 8 points, so the medication group had a mean of M=46 with SS=210 would the data be sufficient to conclude that there is a signficant effect? Use a two tailed test with α= .05

3. Number of Sentences Recalled
Humorus Sentences Nonhumorus Sentences
4 5 2 4 5 2 4 2
6 7 6 6 2 3 1 5
2 5 4 3 3 2 3 3
3 3 5 3 4 1 5 3

a) Do the data provide enough evidence to conclude that humor has a significant effect on memory? Use a two-tailed test at .05 level of significance.
b) Calculate Cohen's d to evaluate the size of the effect.
c) Calulate the precentage of variance explained by the treatment, r2, to measure the effect size.

4) A researcher conducts an independent-measure research study and obtains t=2.070 with df= 28.
a) How many individuals participated in the entire research study?
b) Use a two-tailed test with α=.05, is there a significant difference between the two treatment conditions?
c) Compute r2 to measure the percentage of variance accounted for by the treatment effect.

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Solution Summary

The solution provides step by step method for the calculation of testing of hypothesis, Cohen's d, effect size and pooled variance. Formula for the calculation and Interpretations of the results are also included. Interactive excel sheet is included. The user can edit the inputs and obtain the complete results for a new set of data.

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