Consider a dataset on alcohol consumption and accident fatality. A hypothesis test is performed to establish whether the two variables are independent. In other words, is there a relationship between alcohol consumption and higher accident fatality? The null hypothesis states that alcohol consumption and accident fatalities are independent events, while the alternative hypothesis states the contrary. The product of the row total and column total, divided by the sum of all the frequencies, gives the expected frequency for each table entry. Using the expected and observed values, calculate the chi-square test statistic. Next, with the help of a chi-square table, determine the critical value separating an area of 0.05 in the right tail with one degree of freedom. Since the test statistic is larger than the critical value and falls within the critical region, the null hypothesis – that there is no relationship between alcohol consumption and road accident fatality – is rejected. Thus, at a 5% level of significance, there is sufficient evidence to conclude that alcohol consumption and accident fatality are dependent variables.