Normality test is used to determine whether our sample data has been drawn from a normal distribution population.
A number of statistical tests such as T-Test and the one-way ANOVA and two-way require a normal distribution sample population.
If the assumption of normality is not valid, the results of the tests will be unreliable.
A number of statistical tests such as T-Test and the one-way ANOVA and two-way require a normal distribution sample population.
If the assumption of normality is not valid, the results of the tests will be unreliable.
When we do a normality test?
A lot of statistical tests require that our data are normally distributed and therefore we should always check if this assumption is violated. For example, T-Test
A lot of statistical tests require that our data are normally distributed and therefore we should always check if this assumption is violated. For example, T-Test
Example:
Given a set of data, we would like to check if the
distribution is normal or not.
In this example, we
assume that the null hypothesis is that the data is normally distributed and
the alternative hypothesis is that the data is not normally distributed. The
data set can be obtained here.
The data to be tested in stored in the first column.
- Select Analyze > Descriptive Statistics > Explore
After click, new window will pops out
- From the list above on the left side, select the ‘Data’ variable to the “Dependent List”
- Click “Plots” on the right side and new window will pops out. Click ‘None’ for the “Boxplot” and unclick everything but make sure for descriptive click ‘Normality plots with tests"
- click "OK"
- Last, click “Continue” and the results will pops out in output window
- After the result of normality test is out, we can interpret the result
The test statistics
above shown in the third table are the two tests that always run for normality.
If the data set is small than 30, we use the Shapiro-Wilk test but if the data
set is bigger than 30 the Kolmogorov-Smirnov test is used. In this data, we
used Shapiro-Wilk since the number of data set is 20. From the result, the
p-value show 0.316 > 0.05 so, we reject the alternative hypothesis and
conclude that the data set is normal distribution.
By:
Nur Fariza
References:
Book
Pallant, J. (2013). SPSS survival
manual: A step by step guide to data analysis using SPSS (5th ed.)
Maidenhead: Open University Press/ McGraw-Hill.
Website
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