Answer to Question #317439 in Economics of Enterprise for given

Question

compare the t statics in making inferences to the use of p values

Answer 1

The critical distinction between the T-test and the P-Value is that the T-Test examines the rate of difference between the sample means. A p-value, on the other hand, is utilized to obtain proof that is used to refute the difference in averages between two samples.

For a t-test, the t-value is calculated. The t-test compares the means (averages) of two or more population distributions. The analysis of variance test must be used if there are more than two variables (ANOVA). A p-value is assigned to each t-value to indicate the statistical significance of the difference. There are several sorts of t-tests.

sample t-test

sample t-test

paired t-test

the t-test in regression output

The probability value (p-value) is a numerical metric used to indicate the outcome of statistical hypothesis testing. It aids in calculating the likelihood of the observed outcome (or more extreme) if the null hypothesis (H0) is true for given research, depending on a significance level [typical values for alpha = (0.05, 0.01, 0.001)].(p < alpha). Before beginning the test, it's a good idea to establish the alpha.