Final answer:
In most healthcare-related studies, the alpha is set at 0.05, indicating a 5 percent risk of a Type I error (incorrectly rejecting a true null hypothesis). A p-value less than 0.05 means the null hypothesis can be rejected; if higher, it cannot.
Step-by-step explanation:
The alpha, or "level of statistical significance," is commonly set at 0.05 for most nursing and other healthcare-related studies. The alpha level represents the threshold for rejecting the null hypothesis. A standard alpha level of 0.05 indicates a 5 percent risk of making a Type I error, which is to incorrectly reject a true null hypothesis. When the p-value in a study is less than the set alpha level, researchers conclude that there is sufficient evidence to reject the null hypothesis. As an example, if a study concludes that the mean salary of California registered nurses exceeds $69,110 with a p-value less than 0.05, researchers would reject the null hypothesis at the 5 percent significance level. Contrarily, if the p-value is greater than the alpha level, the decision would be to not reject the null hypothesis, implying insufficient evidence to support a difference from what is stated in the null hypothesis.