Proc Univariate
Proc Univariate Data=DS;
Var var1;
Run;
The first step to data analysis is to look at the shape and distribution of the data.
This can be done by using Proc Univariate.
Example
Copy and run the DEMO data set from the yellow box below.
The DEMO data set contains a list of event participants along with their age and income.
Now, enter and run the code below on SAS Studio:
Example
Proc Univariate Data=Demo;
Var Age;
Run;
By default, Proc Univariate displays 5 sets of statistics:
1. Moment
In statistics, a moment is a measure of the shape of the data.
The first four moments are:
In our example, all four moments are listed in the first table.
2. Basic Statistical Measures
The second table shows the basic statistical measures such as:
3. Tests for Location
The tests for location are the hypothesis testings on whether the population mean is significantly different from zero.
The three tests for locations are:
4. Quantiles
5. Extreme Observations
The statistics give us a good idea of how the data is distributed.
The average age of the events participant is 36.6 with the standard deviation of 12.4.
The skewness is 0.3133, which shows the distribution being slightly skewed to the right.
The kurtosis is 0.1568. This indicates a "flat" distribution as opposed to a "peak" one.
Understanding the distribution of the data is an essential step prior to performing the more complex statistical analysis.
Proc Univariate is a quick way to do just that!
Exercise
Take a look at the DEMO data set again.
Run Proc Univariate on the INCOME variable.
Briefly describe the distribution of the INCOME.
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