American Institute of Certified Planners (AICP) Practice Exam

What does a skewed left distribution imply about the data?

1. Most data points are high

2. A few low numbers pull the mean to the left

3. The data is normally distributed

4. The distribution has a high variance

The correct answer is: A few low numbers pull the mean to the left

A skewed left distribution, also known as a negatively skewed distribution, indicates that most of the data points cluster towards the higher end of the scale, with a tail extending to the left, toward lower values. This characteristic means that while most values are relatively high, there are a few low values that exert a significant influence on the mean, pulling it to the left of the median. In a left-skewed distribution, the mean is typically less than the median because the lower values have a stronger impact on the average due to their position on the number line. Therefore, the statement that a few low numbers pull the mean to the left accurately captures this behavior of the distribution. The other options are not representative of what a left skew implies. Most data points being high is a characteristic but does not explain the skew itself. A normally distributed set of data would not exhibit skewness to either side, and high variance relates to the spread but does not provide insight into the direction of skewness.