Question

Explain what information is produced from a hypothesis test and an estimate of effect size. Why is it important to consider both when interpreting the results of a study?

Answer 1

First of all I would like to explain the type of statistic

The first one is discriptive statistics and the other one is inferential statistics both are different to eachother.

In discriptive statistics we only calculate the mean, median, mode etc. For the central value where as for the variation around the mean we found range, variance, standard deviation etc. Discriptive statistics give us only the overview of the data. If we want to know the difference in mean or relationship among the variable, then discriptive statistics is failed to give the evidence about the difference in mean of the groups or relationship among the variables therefore we need to preform hypothesis testing for this type of problem.

In the hypothesis testing we perform any test to check the difference in mean like t test ANOVA etc. Or for the relationship among the variables we perform the hypothesis test like correlation analysis, regression analysis etc. After performaning the test we concern about the estimate of groups mean and its test probability i.e. P-value. Now we compare the test p-value with the level of significance alpha such as 5% 10% and 1% etc. and we reject or fail to reject the null hypothesis on behalf of the p value. If the p value is less than the level of significance then we fail to reject the null hypothesis and conclude that the mean is differ among the groups or there is significant relationship among the variable.