We present the sampling distributions for the coefficient of skewness, kurtosis, and a joint test of normality for time series observations. We show that when the data are serially correlated, ...

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A general rule of thumb for skewness is that a value below -1.0 or above +1.0 is significant. In this case we have -1.03076 and that is enough to say that the distribution has a negative skew.

Distributions can be positive and right-skewed, or negative and left-skewed. A high skew can reflect the presence of outliers or kurtosis. Two methods that measure skewness include Pearson’s ...