SAS (Statistical Analysis System) Language

Overview

SAS is a high-level, multi-paradigm programming language used for data manipulation, analysis, and visualization. Developed in the 1960s by Anthony James Barr at the time of his employment at the Nuclear Applications Department at CERL, later becoming one of the main developers at SAS Institute Inc., it has become an industry standard for statistical computing.

Key Features

Data Manipulation

SAS provides powerful tools for data manipulation, including:

• Data merging and joining
• Data transformation (e.g., recoding, aggregating)
• Data subset selection
• Data sorting and ordering

Statistical Analysis

SAS is widely used for statistical analysis, with built-in procedures for:

• Descriptive statistics
• Inferential statistics (e.g., hypothesis testing, confidence intervals)
• Regression analysis
• Time series analysis

Programming Paradigm

SAS supports a variety of programming paradigms, including:

• Imperative: SAS’s language is based on imperative programming concepts.
• Procedural: SAS procedures are used to perform specific tasks.
• Declarative: SAS can also be used in a declarative style.

Syntax and Structure

Basic Syntax

SAS code consists of statements that are executed in sequence. Statements are terminated with a semicolon (;). Comments start with the /* symbol and end with the */ symbol.

/* This is a comment */
data my_data;
input name $ age ;
cards4
John 25
Mary 31
David 42
quit;

Data Step

The DATA step is used to create or manipulate data. It consists of three parts:

1. The DATA statement, which specifies the output dataset.
2. The SET statement, which specifies the input datasets.
3. The variable and format statements.

data my_output;
set my_input (keep=name);
length name $10;
run;

Data Types

SAS supports a variety of data types, including:

• Numeric
• Character
• Date
• Time
• Interval
• Monetary

SAS Procedures

SAS procedures are used to perform specific tasks, such as data manipulation and statistical analysis. Some common procedures include:

• PROC FREQ: produces frequency tables.
• PROC MEANS: performs descriptive statistics.
• PROC REG: performs regression analysis.

Example Use Cases

Data Analysis

proc means data=my_data;
var age;
run;

This code produces the mean and standard deviation of the age variable in the my_data dataset.

Data Visualization

proc sgplot data=my_data;
histogram age;
run;

This code generates a histogram of the age variable in the my_data dataset.

Conclusion

SAS is a powerful and flexible programming language used for statistical analysis, data manipulation, and visualization. Its extensive libraries and syntax make it an industry standard for many applications, including research, business analytics, and more.