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Sagot :
The chi-square goodness-of-fit test is a statistical test that is used to determine whether a sample comes from a population with a specific distribution. There are a few conditions that must be met in order to use this test:
1. The data must be collected from a random sample. This ensures that the sample is representative of the population, which is necessary for the test to be valid.
2. The data must be categorical. This means that the observations must fall into distinct categories, rather than being continuous or ordinal.
3. The expected frequencies for each category should be at least 5. This ensures that the chi-square test statistic is approximately normally distributed, which is necessary for the test to be valid.
4. The data must be independent. This means that the outcome of one observation should not influence the outcome of another observation.
If these conditions are not met, the chi-square goodness-of-fit test may not be appropriate. In such cases, it may be necessary to use a different statistical test.
To learn more about data distribution, visit:
brainly.com/question/14926605
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