- SAS Tutorial
- SAS - Home
- SAS - Overview
- SAS - Environment
- SAS - User Interface
- SAS - Program Structure
- SAS - Basic Syntax
- SAS - Data Sets
- SAS - Variables
- SAS - Strings
- SAS - Arrays
- SAS - Numeric Formats
- SAS - Operators
- SAS - Loops
- SAS - Decision Making
- SAS - Functions
- SAS - Input Methods
- SAS - Macros
- SAS - Dates & Times

- SAS Data Set Operations
- SAS - Read Raw Data
- SAS - Write Data Sets
- SAS - Concatenate Data Sets
- SAS - Merging Data Sets
- SAS - Subsetting Data Sets
- SAS - Sort Data Sets
- SAS - Format Data Sets
- SAS - SQL
- SAS - Output Delivery System
- SAS - Simulations

- SAS Data Representation
- SAS - Histograms
- SAS - Bar Charts
- SAS - Pie Charts
- SAS - Scatterplots
- SAS - Boxplots

- SAS Basic Statistical Procedure
- SAS - Arithmetic Mean
- SAS - Standard Deviation
- SAS - Frequency Distributions
- SAS - Cross Tabulations
- SAS - T Tests
- SAS - Correlation Analysis
- SAS - Linear Regression
- SAS - Bland-Altman Analysis
- SAS - Chi-Square
- SAS - Fishers Exact Tests
- SAS - Repeated Measure Analysis
- SAS - One-Way Anova
- SAS - Hypothesis Testing

- SAS Useful Resources
- SAS - Quick Guide
- SAS - Useful Resources
- SAS - Questions and Answers
- SAS - Discussion

- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who

# SAS - Correlation Analysis

Correlation analysis deals with relationships among variables. The correlation coefficient is a measure of linear association between two variables.Values of the correlation coefficient are always between -1 and +1. SAS provides the procedure **PROC CORR** to find the correlation coefficients between a pair of variables in a dataset.

### Syntax

The basic syntax for applying PROC CORR in SAS is −

PROC CORR DATA = dataset options; VAR variable;

Following is the description of the parameters used −

**Dataset**is the name of the dataset.**Options**is the additional option with procedure like plotting a matrix etc.**Variable**is the variable name of the dataset used in finding the correlation.

### Example

Correlation coefficients between a pair of variables available in a dataset can be obtained by use their names in the VAR statement.In the below example we use the dataset CARS1 and get the result showing the correlation coefficients between horsepower and weight.

PROC SQL; create table CARS1 as SELECT invoice, horsepower, length, weight FROM SASHELP.CARS WHERE make in ('Audi','BMW') ; RUN; proc corr data = cars1 ; VAR horsepower weight ; BY make; run;

When the above code is executed, we get the following result −

## Correlation Between All Variables

Correlation coefficients between all the variables available in a dataset can be obtained by simply applying the procedure with the dataset name.

### Example

In the below example we use the dataset CARS1 and get the result showing the correlation coefficients between each pair of the variables.

proc corr data = cars1 ; run;

When the above code is executed, we get the following result −

## Correlation Matrix

We can obtain a scatterplot matrix between the variables by choosing the option to plot matrix in the **PROC** statement.

### Example

In below example we get the matrix between horsepower and weight.

proc corr data = cars1 plots = matrix ; VAR horsepower weight ; run;

When the above code is executed, we get the following result −