SCMA*3040 Lecture Notes - Lecture 7: Skewness, Central Tendency, Kurtosis
Document Summary
Measures of shape: the measures of central tendency will tell you about the central value in your data while measures of variation will tell you how spread is your data from the central value. What about the shape of your data: a histogram provides insight into the shape of a data distribution. However, the to methods that precisely measure the shape of a distribution are skewness and kurtosis. Skewness measures the direction of extreme value in an asymmetrical distribution: kurtosis measures the frequency of extreme value in a symmetrical distribution. Skewness: the relative concentration of data may indicate whether the distribution is symmetrical and asymmetrical. A distribution is called asymmetric when one tail is longer than the other. Skewness measures the asymmetry of a data distribution around its mean: a distribution may skewed towards one direction. Thus, it quantifies how much of the data is skewed to one side of the mean.
