What are some common measures of central tendency, and when would you use each one?

During my final year in college, I worked on a project where we conducted a survey to assess student satisfaction with campus facilities. We collected responses from over 200 students. To summarize the data, I calculated the mean satisfaction score, which gave us a general idea of how students felt overall. However, I noticed that a few outliers—students who rated their satisfaction extremely low—were skewing the mean. To address this, I also calculated the median, which provided a more accurate representation of typical student satisfaction. This taught me the importance of using both measures to present a clearer picture of data.

As a volunteer for a local charity, I helped organize community events. We often tracked attendance to evaluate the success of each event. For one event, I noticed that while the mode of attendees showed that most events attracted around 50 people, the mean was much higher due to a few events that had exceptionally high attendance. By focusing on the mode, we could better understand the typical turnout and plan future events accordingly. This experience reinforced my understanding of when to use the mode as it provided a clearer insight into our community's engagement.

In my first job as a sales assistant, I was responsible for tracking daily sales figures. I noticed that on certain days, sales spiked due to promotions. When analyzing the monthly sales data, I initially calculated the mean to assess overall performance. However, I realized that the mean was inflated by those promotional days. To get a better understanding of our typical sales, I then analyzed the median, which showed me a more stable sales figure. This experience highlighted the importance of selecting the right measure of central tendency based on data distribution.