Summary statistics are a way to capture the main features of a dataset using a few key numbers, such as the mean, median, mode, range, and standard deviation. Understanding these statistics in news reports, blog posts, social media posts, advertisements, and product ratings will help you make sense of the information being presented.

**Mean:**The mean, often referred to as the “average,” is the sum of all data points divided by the number of data points. For example, consider a news article that reports the average salary of a specific job role as $50,000. This means that if you add up all the salaries in that job role and divide by the number of people, you’d get $50,000.**Median:**The median is the middle value in a dataset when the data points are arranged in ascending or descending order. This can accurately represent the “typical” value if the data has extreme values or “outliers.” Imagine reading a blog post about the median home prices in a city. If the median price is $250,000, that means half the homes cost more than that and half cost less.**Mode:**The mode is the value that appears most frequently in a dataset. For example, when looking at product ratings, the mode might be customers’ most common star rating. If a product has a mode of 4 stars, that means the majority of customers gave it a 4-star rating.**Range:**The range represents the difference between a dataset’s highest and lowest values. If a news report mentions that the daily temperature range in a city is 20°F, that means the difference between the highest and lowest temperatures on that day is 20°F.**Standard deviation:**The standard deviation is a measure of how spread out the data points are from the mean. A small standard deviation indicates that the data points are closely clustered around the mean, while a large standard deviation suggests that the data points are more spread out. When reading a study about test scores, if the standard deviation is small, it means most students scored close to the average.