![]() This type of mistake is called a Type II error. Likewise, it is possible that when a difference does exist, the test will not be able to identify it. With any statistical test, however, there is always the possibility that you will find a difference between groups when one does not actually exist. Statistical tests look for evidence that you can reject the null hypothesis and conclude that your program had an effect. Using the example above, the alternative hypothesis is that students’ post-trip level of concern for the environment will differ from their pre-trip level of concern. ![]()
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