Hypothesis Testing Explained - Statistica
Now that you know the null and alternative hypothesis, did you think about what the type 1 and type 2 errors are? It is important to note that Step 1 is before we even collect data. Identifying these errors helps to improve the design of your research study. Let's write them out:
If it is falseI rewrite it as a true statement
Considering , it can be seen that does not lie in the acceptance region of . The null hypothesis, , is rejected and it is concluded that is significant at . This conclusion can also be arrived at using the value noting that the hypothesis is two-sided. The value corresponding to the test statistic, , based on the distribution with 14 degrees of freedom is:
Step Four: Interpret what the p-value is telling you and make a decision using the p-value. Does the null hypothesis provide a reasonable explanation of the data or not? If not it is statistically significant and we have evidence favoring the alternative. State a conclusion in terms of the problem.