When should I use the X2 Goodness-of-fit test (categorical data to compare frequency data with a specific population model)?
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When should I use the X^2 Goodness-of-fit test (two categories and sample sizes too large for a binomial test)? Remember that some tests, such as chi squared, can be used under various circumstances. The goal of the test changes based on the situation. Pay attention to the specific conditions noted in parenthesis to ensure you are picking the correct goal. A. Compare categorical frequency data with an expected population proportion. No difference between observed and expected proportions is used as the null hypothesis. B. Compare two treatment groups consisting of independent samples with a normal distribution AND unequal variance. C. Test the fit of the normal distribution to the data set. D. More than two treatment groups where a normal distribution can be assumed. E. Test to compare frequency data to a specific population model F. Compares numerical data to a known mean. The null hypothesis is that the mean of the data equals the known mean. G. Compare two treatment groups when a normal distribution cannot be assumed. H. Test to see if the frequency data from a population fit a discrete probability distribution. I. Compare two treatment groups consisting of paired data when the data do not fit the normal distribution. J. Compare more than two treatment groups when a normal distribution cannot be met.
Adi S.
When should you use the X Goodness-of-fit test (categorical data to compare frequency data with a specific population model)? Remember that some tests, such as chi-squared, can be used under various circumstances. The goal of the test changes based on the situation. Pay attention to the specific conditions noted in parentheses to ensure you are picking the correct goal. A. Compare two treatment groups when a normal distribution cannot be assumed. B. Compare categorical frequency data with an expected population proportion. No difference between observed and expected proportions is used as the null hypothesis. C. Compare two treatment groups consisting of independent samples with a normal distribution AND unequal variance. D. Compare two treatment groups consisting of paired data when the data do not fit the normal distribution. E. Test to compare frequency data to a specific population model. F. Compare two treatment groups of independent samples where the data meet the assumption that the data fit the normal distribution. Compares numerical data to a known mean. The null hypothesis is that the mean of the data equals the known mean. G. Compare more than two treatment groups where a normal distribution can be assumed. H. Compare two treatments consisting of paired data where a normal distribution can be assumed. I. Test to see if the frequency data from a population fit a discrete probability distribution. J. Compare more than two treatment groups when a normal distribution cannot be met. K. Test the fit of the normal distribution to the dataset. L. Test if the median of a dataset equals the null hypothesized value when the distribution of the data does not meet the assumption of normalcy.
What conditions are necessary to use the chi-square goodness-of-fit test?
Chi-Square Tests and the F-Distribution
Goodness-of-Fit Test
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