Make sure to select the appropriate type of test "Chi-Square test of Goodness-of-fit". An example data set might look like so:ĭice roll observed vs expected frequencies NumberĬlick here to load example data in the calculator and perform a goodness-of-fit test. For example, if we are testing if a dice is fair, we would have an expected frequency of 0.1666(6) for each number. The expected frequencies should sum up to ~1. The chi-square test calculator can be used as a goodness-of-fit calculator by entering the observed values (counts) in the first column and the expected frequencies for each outcome in the second column. If the data is based on two categorical variables measured from the same population the result can be interpreted as a test of independence between the variables. If the sample data is known to be independent the result can be treated as a test of homogeneity. Click here to see how this example works. Simply copy and paste the numerical cells into the calculator's input field above. For example, if you have this data in Excel: The data in all cells should be entered as counts (whole numbers, integers). As a Chi-Square Test of Independence or HomogeneityĬopy/paste the data from a spreadsheet file into the data input field of the calculator or input it manually by using space ( ) as a column separator and new line as a row separator. The mode of operation can be selected from the radio button below the data input field in the Chi Square calculator interface. These modes apply to different situations covered in detail below. The above easy to use tool can function in two main modes: as a goodness-of-fit test and as a test of independence / homogeneity. Comparing the three types of Chi-Square tests.As a Chi-Square Test of Goodness-of-Fit.As a Chi-Square Test of Independence or Homogeneity.
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