Just because two or more values are different does not mean that they are differ

Question

Just because two or more values are different does not mean that they are different in a statistically significant manner. Researchers rely on the p values that are generated for each of their statistical tests to determine significance. If the p value is larger than the alpha, then they are not different in a statistically significant manner, and therefore the values are not considered different. In this journal activity, consider these concepts in terms of the differences between null and alternative hypotheses, and discuss this question: What is the difference between failing to reject the null hypothesis and having evidence to support the alternative hypothesis?

Just because two or more values are different does not mean that they are different in a statistically significant manner. Researchers rely on the p values that are generated for each of their statistical tests to determine significance. If the p value is larger than the alpha, then they are not different in a statistically significant manner, and therefore the values are not considered different. In this journal activity, consider these concepts in terms of the differences between null and alternative hypotheses, and discuss this question: What is the difference between failing to reject the null hypothesis and having evidence to support the alternative hypothesis?

Explanation / Answer

Answer:

When we reject the null hypothesis H0, then there is a sufficient evidence to support the alternative hypothesis. When we do not reject the null hypothesis or failing to reject the null hypothesis Ha, then there is insufficient evidence to support the alternative hypothesis. When we reject the null hypothesis then there is a strong evidence to conclude alternative hypothesis. Most of the times, alternative hypothesis is the researchers main claim which they want to test.

Do not reject null hypothesis means failing to reject null hypothesis.

Reject null hypothesis means there is a evidence to support the alternative hypothesis.

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