Interpreting The P-Value

Microblog

My sister-in-law has a bar-height kitchen table as well as a large bar-height dining table, not to mention her beautiful walnut bar with swivel stools, and that’s just on the first floor.  Hanging out at her home is like going to a cozy modern tavern with the most committed hostess who always has peanut m&m’s at the ready.

One spring evening while sharing a glass of wine with a few of the female members of our famdamily, my niece approached us with a question about her statistics homework. That alone was funny enough, however, when she questioned her mother about interpreting the P-value, we all just about lost it.

Now each of us at the table had a college education, some of us may or may not have taken statistics, but none of us knew or remembered anything about the P-value.

My sister instantly googled P-value “A small P-value (typically ≤ 0.05) indicates strong evidence against the null hypothesis, so you reject the null hypothesis. A large p-value (> 0.05) indicates weak evidence against the null hypothesis, so you fail to reject the null hypothesis.”

I went straight to the Dummies page: When you perform a hypothesis test in statistics, a P-value helps you determine the significance of your results.

So, I’m sure some of you know exactly where this is heading. My poor niece left without anything close to the answer she was looking for. It took us a lot of discussion and a lot of laughs but we determined the amount of wine one drinks directly affects how one interprets the P-value.