Can you describe a situation where you would use a chi-square test instead of a t-test?

In a recent college project, I conducted a survey to understand students' preferences for online versus in-person classes. The data collected were categorical, with options like 'Online', 'In-Person', and 'Hybrid'. To analyze the results, I decided to use a chi-square test, as it helps determine if there's a significant association between students' choices and their year of study. The chi-square test allowed me to see if students in different years had varying preferences, which revealed interesting insights that I later presented to my class.

During my time volunteering for a community health initiative, I helped gather data on the health behaviors of different demographic groups within our community. We wanted to see if there was a relationship between age groups and their smoking habits. With this categorical data, I used a chi-square test to analyze the frequency of smokers versus non-smokers in each age category. The results helped the organization tailor their health campaigns more effectively, ultimately contributing to better public health strategies in our area.

In my first job as a marketing intern, I was tasked with analyzing customer feedback from a recent product launch. The feedback was categorized into 'Positive', 'Neutral', and 'Negative'. I used a chi-square test to assess whether customer satisfaction varied by product version. This analysis revealed significant differences in perceptions between users of different versions, which informed our marketing strategies. This experience reinforced my understanding of choosing the right statistical test based on the nature of the data.