Question

Whether we are conducting a hypothesis test with regards to a one population parameter or two population parameters (usually the difference between two population parameters), the concept of p-value is extremely important in making a decision with respect to the null hypothesis. A very common mistake in elementary statistics is interpreting the p-value of a hypothesis test. Many students think that the p-value is the probability that the null hypothesis is true or that it is the probability of rejecting the null hypothesis: Explain why you think many students erroneously come to these conclusions. In your own words, explain what the p-value represents. What pages of the reading in OLI support your explanation?

Answer 1