Test of Normality using Explore Command

One cannot always be sure of the credibility of the data. In order to understand whether the data is as per the requirement of the user; normality test is conducted.

Testing for Normality

It is an assessment of the normality of data which is a prerequisite for many statistical tests as normal data is a basic hypothesis for testing. There are two main methods of assessing normality –

1.    Graphically

2.    Numerically

In order to determine whether data provided is normal or not and, therefore, the assumption is met in data for statistical tests. The approaches can be divided into two main themes - relying on statistical tests or visual inspection.

1.    Statistical tests have the advantage of making an objective judgement of normality, but are sometimes disadvantaged for not being sensitive enough at low sample sizes or overly sensitive to large sample sizes e.g. if the sample size is two values very far of than each other thus creating a unsuitable mean

     Therefore statisticians use their experience to make a subjective judgement about the data from plots/graphs. Shapiro-Wilk Test of Normality is the test that needs to be done if the sample size is less than 2000.

2.    Graphical interpretation has the advantage of allowing good judgement to assess normality in situations when numerical tests might be over or under sensitive but graphical methods do lack objectivity.

If one is not good at interpreting normality graphically then it is probably best to rely on the numerical methods as they will help one to arrive at acceptable conclusions. Normal Q-Q Plot is the one used in case of Graphical representation

Methods of assessing normality

One can assess normality using spss.

Under Analyze àDescriptive Analysis à Explore Command

The Explore command can be used in isolation if I am testing normality in one group or by splitting the dataset into one or more groups.

For example, if I have a group of participants and I need to know if their height is normally distributed then I will split the group into males and females (assuming that I  have a categorical independent variable) then I can test for normality of height within both the male group and the female group using just the Explore... command.

This applies even if I have more than two groups. However, if I have 2 or more categorical, independent variables then the Explore... command on its own is not enough and I will have to use the Split File... command also.

As we all know that SPSS outputs many table and graphs. One of the reasons for this is that the Explore... command can be used for

1.    Testing of normality and

2.    Describing data in many different ways.

 When testing for normality, one is mainly interested in the Tests of Normality table and the Normal Q-Q Plots, our numerical and graphical methods to test for the normality of data, respectively

This way one can rely on Explore command to come to near accurate conclusions.  










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