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You need to use the distribution with the correct df for your test or confidence interval. Each row of the chi-square distribution table represents a chi-square distribution with a different df. There isn’t just one chi-square distribution-there are many, and their shapes differ depending on a parameter called “degrees of freedom” (also referred to as df or k). To know whether to reject their null hypothesis, they need to compare the sample’s Pearson’s chi-square to the appropriate chi-square critical value. The team wants to use a chi-square goodness of fit test to test the null hypothesis ( H 0) that the four entrances are used equally often by the population. They randomly sample 500 people inside the building and ask them which entrance they used to enter the building. To help them decide where to install the cameras, they want to know how often each entrance is used. Example: A chi-square test case studyImagine that the security team of a large office building is installing security cameras at the building’s four entrances. To find the chi-square critical value for your hypothesis test or confidence interval, follow the three steps below. If you need the left-tail probabilities, you’ll need to make a small additional calculation. The table provides the right-tail probabilities. Use the table below to find the chi-square critical value for your chi-square test or confidence interval or download the chi-square distribution table (PDF).
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Chi-square distribution table (right-tail probabilities)