A researcher wants to know whether athletic women are more flexible than non-athletic women. For this experiment, a woman who exercised vigorously at least four times per week was considered “athletic.” Flexibility is measured in inches on a sit & reach box. A researcher tested his claim using the following summary statistics:| | Athletic women | Non-athletic women ||------------------------|----------------|--------------------|| Sample size (\(n\)) | 50 | 30 || Mean (\(\bar{x}\)) | 5.0 inches | 4.6 inches || Standard deviation (\(s\)) | 1.4 inches | 0.8 inches |Assume that all conditions for testing have been met: \( t = 1.626, p = 0.057 \). At the 1% significance level, state your decision regarding the null hypothesis and your conclusion about the original claim.- **A.** Fail to reject the null hypothesis; there is not strong enough evidence to suggest that athletic women are more flexible, on average, than non-athletic women.- **B.** Fail to reject the null hypothesis; there is strong evidence to suggest that non-athletic women are more flexible, on average, than athletic women.- **C.** Reject the null hypothesis; there is strong evidence to suggest that non-athletic women are more flexible, on average, than athletic women.- **D.** Reject the null hypothesis; there is strong evidence to suggest that athletic women are more flexible, on average, than non-athletic women.

Here, The claim is that athletic women are more flexible than non-athletic women t-statistic is…

Answered: A researcher wants to know whether…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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When should I use the One-sample t-test? Remember that some tests, such as chi squared, can be used under various circumstances. The goal of the test changes based on the situation. Pay attention to the specific conditions noted in parenthesis to ensure you are picking the correct goal. A. Test to compare frequency data to a specific population model B. Compares numerical data to a known mean. The null hypothesis is that the mean of the data equals the known mean. C. Test to see if the frequency data from a population fit a discrete probability distribution. D. Compare two treatment groups when a normal distribution cannot be assumed. E. Compare two treatment groups consisting of paired data when the data do not fit the normal distribution. F. Compare two treatments consisting of paired data where a normal distribution can be assumed. G. Compare two treatment groups of independent samples where the data meet the assumption that the data fit the normal distribution. H. Test the fit of…
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