What do you need to make sure a chi-square test is valid in a 2x2 table? Are the rules different from when it is a larger table?

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The Chi-Square Test of Independence determines whether there is an association between categorical variables (i.e., whether the variables are independent or related). It is a nonparametric test.This test is also known as:Chi-Square Test of Association.This test utilizes a contingency table to analyze the data. A contingency table (also known as a cross-tabulation, crosstab, or two-way table) is an arrangement in which data is classified according to two categorical variables. The categories for one variable appear in the rows, and the categories for the other variable appear in columns. Each variable must have two or more categories. Each cell reflects the total count of cases for a specific pair of categories.Yes, the rules are different from when there it is a large table.The Chi-Square Test of Independence is commonly used to test the following:Statistical independence or association between two or more categorical variables.The Chi-Square Test of Independence can only compare categorical variables.It cannot make comparisons between continuous variables or between categorical and continuous variables. Additionally, the Chi-Square Test of Independence only assesses associations between categorical variables, and can not provide any inferences about causation.1. Two categorical variables.2. Two or more categories (groups) for each variable.3. Independence of observations. (There is no relationship between the subjects in each group. The categorical variables are not &quot;paired&quot; in any way (e.g. pre-test/post-test observations)).4. Relatively large sample size. (Expected frequencies for each cell are at least 1. Expected frequencies should be at least 5 for the majority (80%) of the cells.)

What do you need to make sure a chi-square test

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