After flipping a coin 50 times, there was an observed result of 28 heads and 22 tails. Was the result due to chance, is there something wrong with the coin, or a possible an error in the way the coin is being flipped. The Chi-Square test allows you to answer those questions.
Null Hypothesis – There is no difference between the observed and expected frequency results
The YouTube video goes on to explain the null hypothesis, degrees of freedom, Chi-Square value (0.72) and critical values (3.841)
The whole point of the Chi-Square test is to accept or reject the null hypothesis. You have to either exceed or not exceed the critical value. Because the Chi-Square value (0.72) is lower than the critical value (3.841) you will accept the null hypothesis.
The ChiSquare QlikView App will provide an example of how to create the Chi2-Test using the Statistics Chart Wizard.