Setting Up Hypotheses

This section discusses the logic behind hypothesis testing using concrete examples and explains how to set up null and alternative hypothesis. It explains what Type I and II errors are and how they can occur. Finally, it introduces one-tailed and two-tailed tests and explains which one you should use for testing purposes.

One- and Two-Tailed Tests


  1. Two-tailed tests look for an effect in either direction, so they compute two-tailed probabilities. They are much more common than one-tailed tests in scientific research because an outcome signifying that something other than chance is operating is usually worth noting. Some people disagree with the use of one-tailed tests except in very specific situations.

  2. Because you are interested in the effect in either direction, you will use a two-tailed test. Thus, the null hypothesis is that the mean of the seniors is equal to the mean of the freshmen.

  3. This question is asking you to compute a one-tailed probability. Using the binomial calculator with the values of \mathrm{N}=22, \mathrm{p}=.5, and greater than or equal to 16, you get p=.0262.

  4. This question is asking you to compute a two-tailed probability. The probability that it will come up heads 8 or fewer times is.0081. Multiply that by 2 and you get p =.0162.