You set up an obesity management program in your neighborhood. You wanted to test whether the program affected the BMI of people participating in the program. You measured the BMI level of people participating in your clinic at the beginning of the program and after two months. BMI is measured as a continuous (numeric) variable. Which statistical technique you should conduct to find the effectiveness of your program?

Inferential statistics allow researchers to determine if observed changes in a variable are statistically significant or due to chance. When evaluating the effectiveness of a clinical intervention, the choice of test depends on the data type and the relationship between samples. Continuous variables like BMI require parametric tests if the data is normally distributed. Comparing measurements from the same individuals at different times requires a specific test. Rationale: A. Logistic regression is used to predict the probability of a categorical outcome based on one or more predictor variables. Since the outcome in this study is BMI, which is a continuous numeric variable, logistic regression is an inappropriate choice. It would be used if the outcome were binary, such as "obese" or "not obese." B. The Chi-square test is a non-parametric test used to determine if there is a significant association between two nominal variables. It compares observed frequencies to expected frequencies in a contingency table. Because BMI is measured as a numeric scale and not a category, the Chi-square test cannot be applied to this data. C. An independent t-test is used to compare the means of two unrelated groups, such as a control group versus a treatment group. In this scenario, the measurements are taken from the same group of people at two different times. Using an independent test would ignore the subject-specific variance, leading to an inaccurate statistical conclusion. D. Paired t-test is the correct technique because it compares the means of two related samples. This test is specifically designed for "before and after" studies where each participant serves as their own control. By analyzing the mean difference in BMI for each individual, the test determines if the program had a significant effect.