SAS INTRODUCTION

      SAS

The SAS System is one of the most popular Statistical software for all kinds of data analysis. It is a general purpose statistical package designed for both interactive, non-interactive, and batch uses. 

SAS (Statistical Analysis System) software is comprehensive software which deals with many problems related to Statistical analysis, Spreadsheet, Data Creation, Graphics, etc. It is a layered, multivendor architecture. Regardless of the difference in hardware, operating systems, etc., the SAS applications look the same and produce the same results. The three components of the SAS System are Host, Portable Applications and Data. Host provides all the required interfaces between the SAS system and the operating environment. Functionalities and applications reside in Portable component and the user supplies the Data. We, in this course will be dealing with the software related to perform statistical analysis of data.

      Windows of SAS

• Program Editor : All the instructions are given here.

• Log : Displays SAS statements submitted for execution and messages

• Output : Gives the output generated

      Rules for SAS Statements

• SAS program communicates with computer by the SAS statements.

• Each statement of SAS program must end with semicolon (;).

• Each program must end with run statement.

• Statements can be started from any column.

      SAS Program Functionality:

SAS has scores of statistical and mathematical functions, scores of statistical procedures, macro facility, very flexible data handling capability, and excellent programming capability. SAS can read data in almost any format (e.g., numeric, alphanumeric, binary, dollar, date, time formats), and can read files created using spreadsheet/data base software. It also has excellent data manipulation utilities.

The following is a brief overview of some of the functionalities of SAS:

• Data transformations

• Programming capability

• Macro facility

• Matrix manipulation

• Descriptive Statistics

• Contingency tables

• Correlation

• T-tests

• Univariate & Multivariate ANOVA

• Regression

• General Linear Model

• Nonlinear Regression

• Logistic Regression

• Profit Analysis

• Discriminate Analysis

• Factor Analysis

• Cluster analysis

• Multidimensional scaling

• Forecasting/Time Series

• Nonparametric analysis

• Graphics and graphical interface.