SECTION 6.4 Summary
- -values are more informative than the reject-or-not result of a fixed level test. Beware of placing too much weight on traditional values of , such as .
- Very small effects can be highly signifcant (small ), especially when a test is based on a large sample. A statistically signifcant effect need not be practically important. Plot the data to display the effect you are seeking, and use confidence intervals to estimate the actual value of parameters.
- Many tests run at once will probably produce some signifcant results by chance alone, even if all the null hypotheses are true.