Negative skew, also known as left skew, occurs in a distribution where the tail on the left side is longer or fatter than the right side. This means that most of the data points are concentrated on the right, with fewer values extending to the left. In a negatively skewed distribution, the mean is typically less than the median, which can indicate that there are some lower outliers affecting the overall average. In practical terms, negative skew can be observed in various fields, such as finance or education. For example, if a test has a few very low scores while most students perform well, the distribution of scores may be negatively skewed. Understanding this concept helps in analyzing data trends and making informed decisions.