Chartered Financial Analyst (CFA) Practice Exam Level 2

In statistical hypothesis testing, what does a t-value less than 1.96 indicate?

1. The null hypothesis is rejected

2. The null hypothesis is not significant

3. The alternative hypothesis is confirmed

4. The data perfectly describes the hypothesis

The correct answer is: The null hypothesis is not significant

In the context of statistical hypothesis testing, especially when using a t-test, a t-value is compared to a critical threshold to determine whether to reject the null hypothesis. Typically, a t-value of 1.96 corresponds to the critical value for a two-tailed test at a 95% confidence level. If the computed t-value is less than 1.96, it suggests that the difference observed in the sample data is not statistically significant at the 5% level. Thus, a t-value less than 1.96 indicates that there is not enough evidence to conclude that the effect or difference being tested is significant, leading to the conclusion that the null hypothesis should not be rejected. This aligns with the interpretation of statistical insignificance; the results do not provide sufficient support to accept the alternative hypothesis in favor of the null hypothesis, which remains consistent with the data observed.