186: Skewness in JASP

In this video, we go over the Skewness statistic in JASP. The skewness statistic will tell us if our data is positively or negatively skewed, in comparison to a normal distribution.

A positive statistic will mean a positive skew (the distribution is left-skewed, with a longer right tail), a negative one will mean a negative skew (the distribution is right-skewed, with a longer left tail, and zero represents no skew.  

When it comes to the magnitude of this statistic, there are a few different cutoffs or conventions in the literature. Some are more strict and put the cut-off at -1 to 1 (Bulmer, 1979).

Others are less strict and put that cut off at -2 to 2 (Gravetter & Wallnau, 2014) or -1.5 to 1.5 (Tabachnick & Fidell, 2014).

Bulmer, M. G. (1979). Principles of statistics. Dover Publishing, INC., New York, NY.

Gravetter, F. and Wallnau, L. (2014) Essentials of Statistics for the Behavioral Sciences. 8th Edition, Wadsworth, Belmont, CA.

Tabachnick, B. G., & Fidell, L. S. (2014). Using multivariate statistics. 6th Edition, Pearson.

Related Videos:
187: Kurtosis in JASP 187: Kurtosis in JASP
188: Shapiro-Wilk test of normality in JASP 188: Shapiro-Wilk test of normality i... '

0:00 Intro
0:16 Calculating skewness
0:40 Interpreting skewness statistic

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