Exercise 40 Chi Squared Essay

1282 Words Mar 16th, 2013 6 Pages
Researchers routinely choose an ◊-level of 0.05 for testing their hypotheses. What are some experiments for which you might want a lower ◊-level (e.g., 0.01)? What are some situations in which you might accept a higher level (e.g., 0.1)?
An alpha level of 0.05 is arbitrary and was set as a standard by scientists. One of the key concepts in hypothesis testing is that of significance level or, the alpha level, which specifies the probability level for the evidence to be an unreasonable estimate. Unreasonable means that the estimate should not have taken its particular value unless some non-chance factor(s) had operated to alter the nature of the sample such that it was no longer representative of the population of interest. (Price, 2000)
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So you would have three two effects from this ANOVA: the effect of the ages and the effect of abroad versus local. Using ANOVA in this study, you could also add diet to see if there is any association between cardiac meds, patient’s ages, and differences of abroad versus local. ANOVA creates a way to test several null hypotheses at the same time. (Solutions, 2013)
There are however, certain assumptions that need to be met for true comparison of means prior to conducting the analysis which are:
1. The population in which samples are drawn should be normally distributed.
2. Independent of case: the sample cases should be independent of each other.
3. Homogeneity: Homogeneity means that the variance between the groups should be approximately equal. (Solutions, 2013)
“ANOVA is used very commonly in business, medicine or in psychology research. In business, ANOVA can be used to compare the sales of different designs based on different factors. A psychology researcher can use ANOVA to compare the different attitude or behavior in people and whether or not they are the same depending on certain factors. In medical research, ANOVA is used to test the effectiveness of a drug”. (Solutions, 2013)

References
Chapter Fourteen Analysis of Variance. (2012). Retrieved from

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