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data analysis

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Data Analysis
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Data Analysis
To study the effects of an after-school athletic program in high school students, on the pre-intervention and post-intervention cholesterol levels, the two statistical tests that can be used are the t-tests and chi-square tests. These tests will be done to analyze whether the after-school athletic program changes the cholesterol levels in high school students.
The cholesterol levels before the start of the athletic program will be compared to the cholesterol levels after the end of such athletic program. The null hypothesis contends that there is no significant difference on serum cholesterol before and after the intervention of athletic training program in either sex. Any such difference might have occurred to chances of random sampling (Corder & Foremann, 2014). The null hypothesis will be retained if the p-value of either a t-test or chi-square test is >0.05. This would suggest that out of 100 observations made on serum cholesterol levels before and after implementation of the athletic program, more than five observations revealed that there is no change in serum cholesterol. Hence, the probability of happening by chance is considered very high and null hypothesis is retained (Zimmerman, 1997).
On the other hand the alternative hypothesis or our experimental hypothesis contends that there is significant difference on serum cholesterol before and after the intervention of athletic training program in either sex.

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Any such difference has not occurred to chances of random sampling. The alternative hypothesis will be retained if the p-value of either a t-test or chi-square test is <0.05. This would suggest that out of 100 observations made on serum cholesterol levels before and after implementation of the athletic program, less than five observations revealed that there is no change in serum cholesterol. Hence, the probability of happening by chance is considered very low and the alternative hypothesis would be accepted (Zimmerman, 1997). This would mean that athletic program has significantly changed the serum cholesterol level in both males and females.
References
Corder, G.W. & Foreman, D.I. (2014). Nonparametric Statistics: A Step-by-Step Approach.
Wiley, New York.
Zimmerman, D. (1997). “A Note on Interpretation of the Paired- Samples t Test”.  Journal of
Educational and Behavioral Statistics 22 (3): 349–360.

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