Hypothesis Testing Using t-statistics and Critical Values in Excel

Hypothesis testing using t-statistics and critical values is a statistical method employed to assess the validity of a hypothesis about a population parameter when the sample size is small or when the population standard deviation is unknown. In this approach, a t-statistic is calculated by comparing the difference between the sample mean and the hypothesized population mean, scaled by the standard error of the mean. Excel can be a powerful tool for conducting such tests, as it provides functions like T.TEST and T.INV. Two-tailed tests involve comparing the absolute value of the t-statistic to a critical value from the t-distribution at a specified significance level, typically 0.05. If the calculated t-statistic falls beyond the critical value, the null hypothesis is rejected. Excel simplifies this process by allowing users to input sample data and obtain relevant statistics, facilitating informed decisions about accepting or rejecting a hypothesis based on the comparison of t-statistics and critical values.