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|Table of Contents Statistical Tests Hypotheses Hypothesis Testing|
|See also: types of error, survey on statistical tests, Exploratory Data Analysis|
Hypothesis testing gives us the guidelines for choosing between alternatives by either controlling or minimizing the error associated with the decision. The simplest case for a decision is the 'yes-or-no' question. In court, for example, the jurors have to decide "guilty or not guilty". These statements are two hypotheses. The normal assumption is "not guilty", in statistics this is called the null hypothesis. It is what we normally assume. Then there is an alternative hypothesis, in our example "guilty". We will accept this alternative hypothesis only when there is convincing evidence.
Hypothesis testing can be summarized in the questions: is it reasonable to assume that the value of a population parameter is equal to / larger than / less than x? This question can be applied in various situations. The population parameter can be either the mean or the variance. The value of x is either specified on the basis of prior knowledge, or an estimated parameter from another population.
Hypothesis testing is always a five-step procedure:
Last Update: 2005-Jul-16