Chi-square test
Chi-square test
The Chi-square test (pronounced as Kai-square test) is a statistical test that is used to determine if there is a significant association between two categorical variables in a sample. It is a non-parametric test, which means it does not assume any specific distribution for the data.
Etymology
The term "Chi-square" comes from the Greek letter Chi (Χ), which is used to denote this statistical test. The "square" part of the name comes from the use of the square function in the formula that calculates the test statistic.
Usage
The Chi-square test is commonly used in research to test hypotheses about the relationship between two or more categories of data. It is often used in fields such as medicine, psychology, and sociology to test for independence or association between two categorical variables.
Calculation
The Chi-square test statistic is calculated by comparing the observed frequencies in each category of a contingency table with the frequencies that would be expected if the variables were independent. The formula for the Chi-square test statistic is:
- χ² = Σ [ (O-E)² / E ]
where:
- O is the observed frequency,
- E is the expected frequency.
Related terms
- Contingency table: A table that displays the frequency distribution of several categorical variables.
- Degrees of freedom: The number of independent pieces of information that are needed to calculate the test statistic.
- P-value: The probability of obtaining a test statistic as extreme as the one that was actually observed, assuming that the null hypothesis is true.
See also
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