Hypothesis Testing and P-values

State your null and alternative hypotheses.

The P-value indicates the probability of obtaining results as extreme as the observed results, assuming the null hypothesis is true.

Reject the null hypothesis.

The null hypothesis is a statement that there is no effect or no difference, and it serves as the default assumption.

The alternative hypothesis is a statement that indicates the presence of an effect or a difference.

It means that there is not enough evidence to support the alternative hypothesis.

The significance level is the threshold for determining whether to reject the null hypothesis, commonly set at 0.05.

Since 0.0304 < 0.05, you reject the null hypothesis.

The test statistic formula varies by test, but generally it is (sample mean - population mean) / (standard deviation / sqrt(sample size)).

A Type I error occurs when the null hypothesis is rejected when it is actually true.