Here, we have four steps to use the P-value approach to make the decision for hypothesis test. And, if the P-value is greater than, then the null hypothesis is not rejected. If the P-value is less than (or equal to), then the null hypothesis is rejected in favor of the alternative hypothesis.
#Right right tailed hypothesis test calculator software
It can be shown using either statistical software or a t-table that the critical value is -2.1448 and the critical value is 2.1448. The value is the t-value such that the probability to the left of it is, and the value is the t-value such that the probability to the right of it is.
The critical value for conducting the left-tailed test : versus : is the t-value, denoted, such that the probability to the left of it is α.That is, we would reject the null hypothesis : = 3 in favor of the alternative hypothesis : > 3 if the test statistic is greater than 1.7613. It can be shown using either statistical software or a t-table that the critical value is 1.7613.
The critical value for conducting the right-tailed test : versus : is the t-value, denoted, such that the probability to the right of it is.Suppose we set our significance level at 0.05, so that we have only a chance of making a Type I error. Since, our test statistic has degrees of freedom.
Here we have an example concerning the mean grade point average, suppose we take a random sample of students majoring in mathematics. Critical values correspond to, so their values become fixed when you choose the test's. If the absolute value of your test statistic is greater than the critical value, you can declare statistical significance and reject the null hypothesis. In hypothesis testing, a critical value is a point on the test distribution that is compared to the test statistic to determine whether to reject the null hypothesis.