Skewness And Kurtosis Spss Normality

You can learn more about our enhanced content on our features.

Skewness and kurtosis spss normality. Clicking on options gives you the ability to select kurtosis and skewness in the options menu. Kurtosis tells you the height and sharpness of the central peak relative to that of a standard bell curve. In spss the skewness and kurtosis statistic values should be less than 1 0 to be considered normal. Testing normality in spss.

In order to determine normality graphically we can use the output of a normal q q plot. Those values might indicate that a variable may be non normal. Because of the 4th power smaller values of centralized values y i µ in the above equation are greatly de emphasized. You should now be able to calculate statistics for skewness and kurtosis in spss.

A normal distribution has skewness and excess kurtosis of 0 so if your distribution is close to those values then it is probably close to normal. Kurtosis is sensitive to departures from normality on the tails. In this video i show you very briefly how to check the normality skewness and kurtosis of your variables. Here x is the sample mean.

For skewness if the value is greater than 1 0 the distribution is right skewed. Under the skewness and kurtosis columns of the descriptive statistics table if the statistic is less than an absolute value of 2 0 then you can assume normality of the outcome variable. You can also see that spss has calculated the mean 46 93 metres and the standard deviation 21 122 metres. The skewness statistic is 719 and kurtosis is 125 see above.

The steps for interpreting the spss output for skewness and kurtosis statistics when using anova 1. Hit ok and check for any skew values over 2 or under 2 and any kurtosis values over 7 or under 7 in the output. N represents the number of observations. Just like skewness kurtosis is a moment based measure and it is a central standardized moment.

If you need to use skewness and kurtosis values to determine normality rather the shapiro wilk test you will find these in our enhanced testing for normality guide. Okay that s it for this quick tutorial.