The following format should be used to cite this website tool in APA format:
Theodoros Mprotsis, Chrysoula Doxani, Elias Zintzaras (2022, August). Chi-square test calculation: An interactive calculator for chi-square tests of independence. Available from https://biomath.med.uth.gr.
A researcher frequently wants to know whether the frequency of cases with a particular quality varies between different levels of a particular factor or between different combinations of levels of two or more factors. The chi-square test of independence for k groups is the right test in these circumstances.
If any expected frequency is less than 1, or if the expected frequency is less than 5, in more than 20% of your cells, the chi-square tests should not be used. If there is a problem, it will be indicated in the status window that will pop up after pressing the Calculate button. Expected frequencies of less than 5 are often regarded as acceptable in the 2 x 2 case of the chi-square test of independence if Yates' correction is used.
The white cells should be given the observed frequency. We are aware that not many designs have exactly ten rows and ten columns; if your design is smaller, pick a subset of rows and columns to enter your data in. For instance, if your design is (3 x 4), you might select to enter your data in the 12 cells that the first three rows and the first four columns define in the upper left corner of the data table. The rows and columns in your data set can be any subset that you want. Additionally, you have the option of leaving the cells corresponding to observed frequencies of zero empty. Although it's difficult to fathom how one would actually get non-integer observed frequencies, they are permitted.
However, it is necessary to explicitly incorporate observed zero frequencies (you must enter "0" in such fields else it is presumed that they are not a part of your design). After entering your data, click Calculate, and you should see results in the cells at the right. A pop up window will also appear with the result of chi square in APA format. If your p-value is written in scientific notation, there is no need to be worried; it merely indicates that p is very little.