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Hypothesis testing learning notes
2022-07-06 06:03:00 【Zhan Miao】
1. The basic concept of hypothesis testing
1.1. The null hypothesis ( Null hypothesis )
The assumption made about the distribution of the population is Express , It is also called original hypothesis or null hypothesis
When the overall distribution type is known , Statistical assumptions involving only unknown parameters in the population distribution , It is called parameter hypothesis
When the overall distribution type is unknown , Statistical assumptions about the type of population distribution or some characteristics of population distribution , It is called nonparametric hypothesis
1.2. Two types of errors in hypothesis testing
2. Significance test of single normal population parameter
Yes, hypothesis A test of depends entirely on small probability events A The choice of .
2.1. μ test
When the variance is known, the significance test of the mean value of a normal population can be summarized into the following steps :
2.2. t test
2.3. test
3. Significance test of two normal population parameters
3.1. F test
Significance test table of normal population parameters
4. Nonparametric hypothesis test
Goodness of fit test
Pearson statistics
To sum up, use Goodness of fit test to test the hypothesis about the overall distribution , Steps are as follows :
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