The minimum or maximum value that one would expect the test statistic to yield if the null hypothesis is true is an example of which of the following
What following?
The minimum or maximum value that one would expect the test statistic to yield if the null hypothesis is true is an example of which of the following:
1) Critical Value
2) value
3) t-test score
4) sampling mean
The minimum or maximum value that one would expect the test statistic to yield if the null hypothesis is true is an example of a critical value.
To understand this, let's first clarify some terms:
1. Null Hypothesis: In statistical hypothesis testing, the null hypothesis (H0) represents the assumption that there is no significant difference or relationship between variables.
2. Test Statistic: The test statistic is a numerical summary of the data that is used in hypothesis testing. It is calculated from the sample data and provides evidence for or against the null hypothesis.
3. Critical Value: In hypothesis testing, the critical value(s) define the boundaries for decision-making. They are specific values on the test statistic's distribution that determine when to reject or fail to reject the null hypothesis.
Now, back to your question. The minimum or maximum value that one would expect the test statistic to yield if the null hypothesis is true refers to the extreme values on the distribution of the test statistic under the null hypothesis. These extreme values are called critical values.
Critical values are determined based on the significance level (alpha) chosen for the hypothesis test. They represent the cutoffs that divide the rejection region (where the null hypothesis is rejected) from the non-rejection region (where the null hypothesis is not rejected).
To find the critical value(s), you need to consult a reference table or use statistical software. The specific critical value(s) depend on the nature of the hypothesis test and the distribution of the test statistic (e.g., t-distribution, z-distribution).
In summary, the minimum or maximum value that one would expect the test statistic to yield if the null hypothesis is true is an example of a critical value, which defines the boundary for decision-making in hypothesis testing. Critical values can be obtained from reference tables or statistical software based on the chosen significance level.