9 Hypothesis Testing
When interpreting an experimental finding, a natural question arises as to whether the finding could have occurred by chance.
Hypothesis testing is a statistical procedure for testing whether chance is a plausible explanation of an experimental finding.
A statistical hypothesis is an assumption about a population parameter. This assumption may or may not be true.
Hypothesis testing refers to the formal procedures used by statisticians to accept or reject statistical hypotheses.
The best way to determine whether a statistical hypothesis is true would be to examine the entire population. Since that is often impractical, researchers typically examine a random sample from the population. If sample data are not consistent with the statistical hypothesis, the hypothesis is rejected6.
In other words, to understand some characteristic of the general population we take a random sample and study the corresponding property of the sample. We then determine whether any conclusions we reach about the sample are representative of the population.
This is done by choosing an estimator function for the characteristic (of the population) we want to study and then applying this function to the sample to obtain an estimate. By using the appropriate statistical test we then determine whether this estimate is based solely on chance7.