A research report summarizes the results of the hypothesis test by stating, "t(45) = 1.31, p > .05." If ⍺ =.05, what happened in this study?
Question 19 options:

The null hypothesis was rejected

The null hypothesis was not rejected

Not enough information to determine

In this study, the null hypothesis was **not rejected**. 

Here’s why:

- The test statistic is given as **t(45) = 1.31**, where 45 is the degrees of freedom (df).
- The p-value is reported as **p > .05**.
- The significance level (⍺) is **.05**.

Since the p-value is greater than the significance level (p > .05), there is not enough evidence to reject the null hypothesis. In hypothesis testing, when p > ⍺, it means the result is not statistically significant, and we fail to reject the null hypothesis.

### Conclusion: The null hypothesis was not rejected.

Would you like more details on hypothesis testing or any related concepts? 

Here are 5 related questions:
1. What does a p-value represent in hypothesis testing?
2. How do you calculate the degrees of freedom in a t-test?
3. What happens when the p-value is less than ⍺?
4. How is the t-statistic calculated in hypothesis testing?
5. What are Type I and Type II errors in hypothesis testing?

**Tip**: Always check both the p-value and significance level when interpreting the results of a hypothesis test.

A research report summarizes the results of the hypothesis test by stating, 't(45) = 1.31, p > .05.' If ⍺ = .05, what happened in this study?

Understand how to interpret the results of a hypothesis test with t(45) = 1.31 and p > .05, where the null hypothesis was not rejected at the ⍺ = .05 significance level. Explore key statistical concepts such as t-statistics, p-values, and hypothesis testing. Suitable for introductory college statistics students.

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