Which is better? Which has more? Do people really differ? Quantitative questions like these dominate the polite conversations of our times. If you want some real evidence for your beliefs about the best, most, and least, you can use a statistical tool called the "t test" to support your point.
My Uncle Frank is full of opinions. Green M&Ms taste better than blue. Women never get speeding tickets. The Brady Bunch kids could sing better than the Partridge Family. Plaid is back. He can argue all day spouting half-baked idea after half-baked idea. While I disagree with him on all four points (especially the position that plaid is back—after all, it never left!), I have only my opinions to fight with.
If only there were some scientific way to prove whether Uncle Frank is right or wrong! You no doubt recognize the rhetorical nature of my plea. After all, there are only about a gazillion statistical tools that exist to test hypotheses like these. One of the simplest tools is designed to test the simplest of claims. If the problem is deciding whether one group differs from another, the procedure known as an independent t test is the best solution.
To apply a t test to investigate one of Uncle Frank's theories, we have to compute a t value. Let's imagine that I decided to actually challenge Uncle Frank and collect some data to see whether he is right or wrong.
Uncle Frank believes that males get speeding tickets more frequently ...