Is the alternative hypothesis the rejection region?
The rejection region is based on the alternative hypothesis. The rejection region is the region where, if our test statistic falls, then we have enough evidence to reject the null hypothesis.
What does it mean when the alternative hypothesis is rejected?
When your p-value is less than or equal to your significance level, you reject the null hypothesis. The data favors the alternative hypothesis. Your results are statistically significant. When your p-value is greater than your significance level, you fail to reject the null hypothesis.
Can the alternative hypothesis be rejected?
As for the alternative hypothesis, it may be appropriate to say “the alternative hypothesis was not supported” but you should avoid saying “the alternative hypothesis was rejected.” Once again, this is because your study is designed to reject the null hypothesis, not to reject the alternative hypothesis.
What is alternative hypothesis in hypothesis testing?
In statistical hypothesis testing, the alternative hypothesis is a position that states something is happening, a new theory is preferred instead of an old one (null hypothesis). Hypotheses are formulated to compare in a statistical hypothesis test.
How to test the rejection region of a hypothesis?
The rejection region method 1 Express the claim about a specific value for the population parameter of interest as a null hypothesis, denoted NH. 2 Express the alternative claim as an alternative hypothesis, denoted AH. 3 Calculate a test statistic based on the assumption that the null hypothesis is true.
When to reject the null hypothesis or the alternative hypothesis?
Make decision: Since the p-value is between 0.01 and 0.025, it must be less than the significance level (0.05), so we reject the null hypothesis in favor of the alternative.
When to reject the null hypothesis in upper tail test?
This region, which leads to rejection of the null hypothesis, is called the rejection region. For example, for a significance level of 5%: For an upper-tail test, the critical value is the 95th percentile of the t-distribution with n−1 degrees of freedom; reject the null in favor of the alternative if the t-statistic is greater than this.
Which is on the right side of the reject region?
In this situation, the rejection region is on the right side. So, if the test statistic is bigger than the cut-off z-score, we would reject the null, otherwise, we wouldn’t. To sum up, the significance level and the reject region are quite crucial in the process of hypothesis testing.