Chi-squared test determines whether there is a significant difference between the expected frequencies and the observed frequencies in different categories. We gather observed frequencies using your data. Then we calculate expected frequencies.

To count expected frequencies, we use following equation:

where *n *is number of
observations, n_{ij} is value in row *i* and column *j*, is summary of values in row *i*, and is summary of values in column *j*.

We can do this test in R Studio, which will calculate everything for us without the need to follow steps above). The most important value is p-value. If p-value of chi-square test is bigger than 0,05, it means that difference between answers is not statistically significant.

Assumptions of chi square test are: data should have at least 40 observations and at least 80 % of the observed frequencies should be bigger than 5.