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**Data Analysis [1-15]**

**Proc Univariate**

Proc Univariate is commonly used in Exploratory Data Analysis.

It provides a full set of statistics for you to understand the distribution of the data.

Copy and run the

It provides a full set of statistics for you to understand the distribution of the data.

__Example__Copy and run the

**DEMO**data set from the yellow box below.Open the

**DEMO**data set in SAS Studio.

The 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:

- 1st: Mean
- 2nd: Variance
- 3rd: Skewness
- 4th: Kurtosis

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:

- Mean
- Median
- Mode
- Standard Deviation
- Variance
- Range
- Interquartile Range

**3. Tests for Location**

The three tests for locations are:

- Student’s test
- sign test
- Wilcoxon signed rank test

**4. Quantiles**

5. Extreme Observations

5. Extreme Observations

The statistics give us a good idea 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 "flag" 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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