参数假设检验中的零假设和替代假设，总体分布类型是已知的。 假设检验的目

The null hypothesis and alternative hypothesis in the parametric hypothesis test, the type of population distribution is known. The purpose of hypothesis testing is to test population parameters. To this end, researchers need to put forward some assumptions before they can judge whether the assumptions are correct based on sample statistics. In parameter hypothesis testing, "hypothesis" is a statement made about the specific value of the entire parameter. In order to make sample statistics inevitably support and only support one hypothesis, the logical integrity of a pair of hypotheses and the mutually exclusive overall parameters, namely the null hypothesis (called h0h 0h0), the alternative hypothesis (alternative hypothesis), (Expressed as h1h 1h1)

The parameter hypothesis test sits with zero and alternative assumptions, and the population distribution type is known. The purpose of the hypothesis test is to test the population parameters. To do this, researchers need to make some assumptions before they can determine whether they are correct based on sample statistics. In the parameter hypothesis test, "assumption" is a statement of the specific value of the entire parameter. In order for the sample statistics to inevitably support and support only one hypothesis as evidence, a pair of assumptions for logical integrity and mutually exclusive overall parameters, namely zero assumptions (called h0h 0h0), alternative assumptions (alternative assumptions), expressed as h1h 1h1)

The type of population distribution is known for zero hypothesis and alternative hypothesis in parameter hypothesis test. The purpose of hypothesis testing is to test population parameters. Therefore, researchers need to put forward some hypothesis, and then judge whether the hypothesis is correct according to the sample statistical data. In the parameter hypothesis test, "hypothesis" is a statement of the specific value of the whole parameter. In order to make the sample statistics as evidence inevitably support and only support one hypothesis, the logical integrity of a pair of hypotheses and the overall parameters of mutual exclusion, namely zero hypothesis (called h0h0), alternative hypothesis (alternative hypothesis), expressed as h1h 1h1)<br>