In a Chi Square test, what do high discrepancies between observed and expected frequencies indicate?

In a Chi Square test, high discrepancies between observed and expected frequencies indicate a potential rejection of the null hypothesis. This statistical test is used to determine whether there is a significant difference between the expected frequencies and the frequencies actually observed in data. When the observed frequencies deviate substantially from the expected frequencies, it suggests that the null hypothesis – which posits that there is no association between the categorical variables being analyzed – may not be true. In other words, significant differences imply that the variables might be related in some way, warranting further investigation into the relationship and potentially leading to a rejection of the null hypothesis. This insight is crucial for researchers to understand how their data fits within the context of their hypotheses.