What is the difference between mean, median, and mode, and in what scenarios would you prefer one measure of central tendency over the others?

During my final year in college, I worked on a project where we surveyed students about their study habits. We collected data on hours studied per week. After analyzing the data, I calculated the mean, median, and mode. The mean was skewed due to a few students who studied over 40 hours a week, which wasn’t typical. Hence, I chose to use the median to present a better central point that reflected the majority of students studying around 15 hours a week. This experience taught me the importance of choosing the right measure depending on the data distribution.

While working part-time at a retail store, I was responsible for tracking sales of different products. I noticed that one product sold exceptionally well during promotions, affecting the overall sales average. Instead of using the mean to measure the typical sales, I decided to use the mode, which showed the most frequently sold item. This helped the management to better understand customer preferences and adjust inventory accordingly. This experience highlighted how the mode can be more practical in certain retail scenarios where frequency matters more than the average.

In my first job as a data analyst, I was tasked with evaluating employee performance metrics. The team had a couple of exceptionally high performers whose results skewed the mean performance score. In meetings, I suggested using the median to give a clearer picture of the typical performance. This approach helped management identify areas for improvement among the majority of employees without being misled by outliers. This experience emphasized the importance of context in choosing the right statistical measure.