Pearson Coefficient Of Skewness Formula Software Programs Perform

Skewness is a measurement of symmetry where kurtosis is a measure of peaknessflatness.

The use of a histogram will give a quick visual indication of the skewness and kurtosis.

A normal distribution has a skewness and kurtosis 0 (Mesokurtic is the term for a kurtosis 0).

If: Sk 0 then skewed right distribution Sk 0 then normal distribution Sk.

A visualization and calculation of kurtosis and skewness is used to help make that decision.

It is one of many tools (others include the p-value or the fat-pencil tests) to determine whether a distribution is normal.

Pearson Coefficient Of Skewness Formula Software Programs Perform

Most software programs perform these calculations but each has a specific formula that may be important to understand if you are weighing heavily on it to make a decision.

If your data doesnt meet the assumptions for normality, there are tools such as a Box-Cox transformation, log, square root of data to make a data set more normal and the apply the normality tests to the transformed data.

The histogram and curve creates a visualization which shows the data is highly unlikely to meet the assumptions of normality.

The p-value also is further evidence being very low and most likely much less than the chosen alpha-risk (most often 0.05).

The importance of graphing is illustrated in this example.

This requires further investigation from the Six Sigma project manager.

On another note: The kurtosis is negative which is another characterization of the data distribution shape.

When the value is negative the shape is referred to as Platykurtic which indicates flatter distribution that normal bell curve.

The p-value is also is further evidence being very low and most likely much less than the chosen alpha-risk (most often 0.05).

On another note: The kurtosis is positive which is another characterization of the data distribution shape.

When the value is positive the shape is called Leptokurtic which indicates peaked shaped distribution compared to normal bell curve.

The formula compares the sample median with the standard deviation of the same distribution.

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