Chi Square Pearson Test. It is the most widely used of many chi squared tests e g yates likelihood ratio portmanteau test in time series etc statistical procedures whose results are evaluated by reference to the chi squared distribution. It is used when categorical data from a sampling are being compared to expected or true results.
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This test is used when we have categorical data for two independent variables and we want to see if there is any relationship between the variables. A chi square test is designed to analyze categorical data. For example to see if the distribution of males and females differs between control and treated groups of an experiment requires a pearson s chi square test.
Pearson s chi squared test is used to determine whether there is a statistically significant difference between the expected frequencies and the observed frequencies in one or more categories of a contingency table.
The expected values are calculated based on the known theoretical expectation. That means that the data has been counted and divided into categories. The pearson chi square statistic χ 2 involves the squared difference between the observed and the expected frequencies. Let s take another example to understand this.
