University of Toronto (UofT) PSY201 Statistics I Midterm 1 Practice Exam

A higher skewness indicates a greater degree of asymmetry in the distribution. In statistics, skewness measures the direction and the degree of distortion from the symmetrical bell curve of a normal distribution. When a distribution is skewed, it means that it leans more to one side—either positively or negatively—indicating that the data points are not evenly distributed around the mean.

For example, a positively skewed distribution has a longer tail on the right side, while a negatively skewed distribution has a longer tail on the left side. Thus, a higher skewness reflects a more pronounced asymmetry, which can significantly affect the mean and median of the dataset. Understanding the skewness of a distribution is crucial as it helps in determining suitable statistical methods and tests for data analysis.