Suppose that Dietitians recently recommended a 400 cal per meal and take her children of the age of the data set. To see if both groups adhere to the guideline follow the steps to develop and test a statistical hypothesis. Test to see if us groups means are different from 400 calories. You have two data sets so you'll be completing the process twice. Use 0.05 as a level of significance and make sure to report any important statistic with your results (e.g., mean of each group, standard deviation of each group, test stastistic (are you using t or z?), rejection region and p value). 1. State null and alternative hypothesis. 2. choose level of significance (alpha value) 3. Select the appropriate test stastic.
Suppose that Dietitians recently recommended a 400 cal per meal and take her children of the age of the data set. To see if both groups adhere to the guideline follow the steps to develop and test a statistical hypothesis. Test to see if us groups means are different from 400 calories. You have two data sets so you'll be completing the process twice. Use 0.05 as a level of significance and make sure to report any important statistic with your results (e.g., mean of each group, standard deviation of each group, test stastistic (are you using t or z?), rejection region and p value).
1. State null and alternative hypothesis.
2. choose level of significance (alpha value)
3. Select the appropriate test stastic.
4. draw the rejection region
5. collect the data, calculate the appropriate test statistic and determine if it falls within the region of rejection or non-rejection.
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