# Skewness and kurtosis

## Skewness and kurtosis statistics are used to assess the assumption of normality

**Skewness**and

**kurtosis**statistics are used to assess the

**normality**of a continuous variable's distribution. The statistical assumption of normality must always be assessed when conducting inferential statistics with continuous outcomes.

Any skewness or kurtosis statistic

**above an absolute value of 2.0**is considered to mean that the distribution is

**non-normal**. Skewness and kurtosis statistics

**below an absolute value of 2.0 denote a normal distribution**.

### The steps for conducting skewness and kurtosis statistics in SPSS

1. Click

2. Drag the mouse pointer over the

3. Select

4. Click on the continuous outcome variable to highlight it.

5. Click on the

6. Click the

7. Deselect

8. Select the

9. Click

10. Select the

11. Click

**.**__A__nalyze2. Drag the mouse pointer over the

**D**drop-down menu.__e__scriptive Statistics3. Select

**.**__D__escriptives4. Click on the continuous outcome variable to highlight it.

5. Click on the

**arrow**to move the outcome variable into the**box.**__V__ariable(s):6. Click the

**tab.**__O__ptions7. Deselect

**Mi**and__n__imum**Ma**boxes under the__x__imum**Dispersion**section.8. Select the

**and**__K__urtosis**Ske**boxes under the__w__ness**Distribution**section.9. Click

**Continue**.10. Select the

**Save standardi**box.__z__ed values as variables11. Click

**OK**.### The steps for interpreting the SPSS output for skewness and kurtosis statistics

1. Under the

**skewness**and**kurtosis**columns of the**Descriptive Statistics**table, if the**Statistic is less than an absolute value of 2.0**, then one can assume**normality**of the variable.## Hire A Statistician - Statistical Consulting for Professionals

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