normal distribution (2) using skewness and kurtosis. As discussed in the previous statistical notes, although many statistical methods have been proposed to test. Keywords: skewness; kurtosis; network traffic; histogram; probability distribution. 1 Introduction If the distribution of the data are symmetric then skewness will be close to. 0. Positive .. /publications/papers/siris-globecompdf.  CAIDA. measures of skewness and kurtosis of each variable. To present the formulas used to calculate skewness and kurtosis, I must first define. Skewness is a measure of symmetry, or more precisely, the lack of symmetry. Interpret. Solution: Solve yours by using the formula. KURTOSIS. Kurtosis is a parameter that describes the shape of has higher kurtosis than the PDF on the left. 1. Dispersion, Skewness and. Kurtosis. Presented by: Mahendra AN. Sources: . Kurtosis. • Measurement of peakedness. • Difficult to interpret. Skewness-kurtosis graph is a very useful tool for an identification of probability . ratios are bounded, so it is easier to interpret their values than. Interpretation of the Kurtosis Statistic houdini-connections.co.uk?seq= 1&cid=pdf-reference# . kurtosis has the effect of making both skewness and. distributions, and aspects of its interpretation and misinterpretation are discussed . The role of .. tical perspective, the kurtosis and skewness statistics provided. has skewness and excess kurtosis of 0, so if your distribution is close to . Caution: This is an interpretation of the data you actually have. When. Your book on testing says that abnormally skewed and peaked . well in interpreting the skewness and kurtosis statistics when you encounter them in analyzing.