Can you describe a situation where you would use a chi-squared test versus a t-test?

During my statistics course, I conducted a project analyzing student preferences for different study methods. I collected survey data from 100 students, asking whether they preferred group study or solo study. Since this data was categorical, I used a chi-squared test to determine if there was a significant difference in preferences between different majors. The results showed that students from different majors had varying preferences, which I presented in my project. This experience helped me understand how to apply statistical tests based on data types.

While volunteering at a local nonprofit, I helped evaluate the effectiveness of a tutoring program. We collected test scores from two groups of students: those who participated in the program and those who did not. To compare their test scores, which were continuous data, I used a t-test to determine if there was a significant difference in performance. The analysis showed that the program was effective, and this finding was crucial for securing more funding. This experience taught me how to use statistical analysis to make informed decisions.

In my first job as a marketing assistant, I analyzed customer feedback on two different advertising campaigns. The feedback scores were continuous data, so I used a t-test to compare the average satisfaction scores from both campaigns. The results indicated that one campaign was significantly more effective than the other, which led to the decision to allocate more resources to the successful campaign. This experience reinforced the importance of selecting the right statistical test to derive useful insights.