Q5 : In a cross-sectional study on coronary heart disease (CHD), the smoking and CHD status are summarized below

To find any association between two sets of data here smoking and CHD a chi square test for independence is generally used(What Is a Chi-Square Test? Formula, Examples & Uses | Simplilearn, n.d.). Assumptions- The information must be gathered through random sampling. Instead of percentages or other data transformations, the data in the cells should be frequencies or counts of the cases. The variables' levels (or categories) are mutually exclusive. Applications- As it applies to categorical variables, chi-square is most frequently utilized by researchers who are analyzing survey response data. This kind of study includes, among other things, demographics, consumer and marketing research, political science, and economics. A two-tailed test allocates half of the alpha to testing the statistical significance in one direction and half of the alpha to testing the statistical significance in the other direction if we are employing a significance level of 0.05. This implies that our test statistic's distribution has 0.025 in each tail. When testing a hypothesis, the statistical significance of the data is quantified using the probability (p) value. P values, which range from 0 to 1, indicate the likelihood of getting extreme findings when the null hypothesis is true. The less likely it is to get such severe results when the null hypothesis is correct, the lower the p value. The null hypothesis is rejected when the statistical analysis's calculated p value is less than 0.05 (5%). In hypothesis testing, the 0.05 (5%) significance cut-off (level) is regarded as the norm.