Every time you conduct a hypothesis test, there are four possible outcomes of your decision to reject or not reject the null hypothesis: (1) You don't reject the null hypothesis when it is true, (2) you reject the null hypothesis when it is true, (3) you don't reject the null hypothesis when it is false, and (4) you reject the null hypothesis when it is false.Consider the following analogy: You are a meat inspector for the county health department. For every batch of meat you inspect, you must decide whether to certify that the meat is safe for human consumption. Suppose your null hypothesis is that the meat is unfit for human consumption. As in hypothesis testing, there are four possible outcomes of your decision: (1)You do not certify the meat when the meat is unfit for human consumption, (2) you certify the meat when the meat is unfit for human consumption, (3) you do not certify the meat when the meat is safe, and (4) you certify the meat when the meat is safe.

Which of the following outcomes corresponds to a Type I error?

You do not certify the meat when the meat is safe.

You do not certify the meat when the meat is unfit for human consumption.

You certify the meat when the meat is unfit for human consumption.

You certify the meat when the meat is safe.

Which of the following outcomes corresponds to a Type II error?

You do not certify the meat when the meat is unfit for human consumption.

You certify the meat when the meat is unfit for human consumption.

You do not certify the meat when the meat is safe.

You certify the meat when the meat is safe.

As a meat inspector, the worst error you can make is to certify the meat when the meat is unfit for human consumption. The probability that you make this error, in our hypothesis testing analogy, is described by .