The three commonly used alpha levels are p=01, p=05, and p=10
a. Explain what each level means.
b. Which one of the three is more frequently used in research?
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P = probability that the results would occur solely on the basis of chance (alpha error). This is the likelihood of rejecting the null hypothesis, when the null hypothesis is really true.
Check various research projects to get an idea of which level of significance is used. However, I would be on .05. (By the way, the decimal point does make a difference.)
a. The alpha level in statistics represents the significance or critical region used in hypothesis testing. It determines the threshold at which we reject or fail to reject the null hypothesis.
- A p=0.01 alpha level means that we are willing to accept a 1% risk of making a Type I error (also known as a false positive). It indicates that if the p-value (probability value) of our statistical test is less than 0.01, we reject the null hypothesis.
- A p=0.05 alpha level means that we are accepting a 5% risk of making a Type I error. If the p-value is less than 0.05, we reject the null hypothesis.
- A p=0.10 alpha level means that we are willing to accept a 10% risk of making a Type I error. In this case, we reject the null hypothesis if the p-value is less than 0.10.
b. Among the three commonly used alpha levels, the p=0.05 level is more frequently used in research. It is a widely accepted standard in most scientific fields. The choice of alpha level depends on the study's objectives, the potential consequences of Type I and Type II errors, and the specific field of research. The p=0.05 alpha level strikes a balance between minimizing Type I and Type II errors, making it a common choice. However, it's important to note that the appropriate alpha level should be determined based on context and considered carefully in each research study.