Why it is important to find the shape of data distribution before computing descriptive statistics?

It is important to find the shape of data distribution before computing descriptive statistics because different types of distributions have different properties. For example, a normal distribution is symmetrical and has an average value that is the same as its median; whereas a skewed distribution has an asymmetrical shape and will have a mean that is higher or lower than its median. Understanding the shape of data helps us to understand which measures are most appropriate for summarizing the data (e.g., mean vs median). It also helps us identify any outliers or other points in the dataset that may be skewing results and impacting our interpretation of the data.