What is Critical Value?
Critical values are essential components in hypothesis testing. They are calculated to help determine the significance of test statistics in relation to a specific hypothesis. The distribution of these test statistics guides the identification of critical values. In a one-tailed hypothesis test, there is one critical value, while in a two-tailed test, there are two critical values, each corresponding to a specific level of significance.
Critical Value Definition
Critical values are often defined as specific points on a scale used in statistical tests. These points help determine whether the results of a test are statistically significant or not. They serve as thresholds for making decisions about hypotheses being tested.
Critical Value
Critical value is a cut-off value used to mark the beginning of a region where the test statistic obtained in the theoretical test is unlikely to fail. Compared to the obtained test statistic to determine the critical value at hypothesis testing, Null hypothesis is rejected or not. Graphically, the critical value divides the graph into an accepted and rejected region for hypothesis testing. It helps to check the statistical significance of the test statistics. So, critical values are simply the function’s output at these critical points.
In this article, we will learn more about the critical value, its formula, types, and how to calculate its value.
Table of Content
- What is Critical Value?
- Critical Value Formula
- T-Critical Value
- Z-Critical Value
- F-Critical Value
- Chi-Square Critical Value