The chi-squared goodness of fit test determines whether an observed categorical variable follows an expected distribution. The test’s null hypothesis states that the variable follows the expected distribution. The alternative hypothesis states that the variable doesn’t follow the expected distribution.
The chi-squared test for independence determines whether two categorical variables are associated with each other. The test’s null hypothesis is that the variables are independent. The alternative hypothesis states that the variables are not independent and are therefore associated with each other.
The chi-squared statistic equals the sum of the observed number minus the expected number, squared, divided by the expected number.
The chi-squared goodness of fit test determines whether an observed categorical variable follows an expected distribution.
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