- SAS - Dates & Times
- SAS - Macros
- SAS - Input Methods
- SAS - Functions
- SAS - Decision Making
- SAS - Loops
- SAS - Operators
- SAS - Numeric Formats
- SAS - Arrays
- SAS - Strings
- SAS - Variables
- SAS - Data Sets
- SAS - Basic Syntax
- SAS - Program Structure
- SAS - User Interface
- SAS - Environment
- SAS - Overview
- SAS - Home
SAS Data Set Operations
- SAS - Simulations
- SAS - Output Delivery System
- SAS - SQL
- SAS - Format Data Sets
- SAS - Sort Data Sets
- SAS - Subsetting Data Sets
- SAS - Merging Data Sets
- SAS - Concatenate Data Sets
- SAS - Write Data Sets
- SAS - Read Raw Data
SAS Data Representation
SAS Basic Statistical Procedure
- SAS - Hypothesis Testing
- SAS - One-Way Anova
- SAS - Repeated Measure Analysis
- SAS - Fishers Exact Tests
- SAS - Chi-Square
- SAS - Bland-Altman Analysis
- SAS - Linear Regression
- SAS - Correlation Analysis
- SAS - T Tests
- SAS - Cross Tabulations
- SAS - Frequency Distributions
- SAS - Standard Deviation
- SAS - Arithmetic Mean
SAS Useful Resources
Selected Reading
- Who is Who
- Computer Glossary
- HR Interview Questions
- Effective Resume Writing
- Questions and Answers
- UPSC IAS Exams Notes
SAS - Simulations
Simulation is a computational technique that uses repeating computation on many different random samples in order to estimate a statistical quantity. Using SAS we can simulate complex data that have specified statistical properties in real-world system. We use software to build a model of the system and numerically generate data that you can be used for a better understanding of the behavior of the real-world system. Part of the art of designing a computer simulation model is deciding which aspects of the real-pfe system are necessary to include in the model so that the data generated by the model can be used to make effective decisions. Because of this complexity, SAS has a dedicated software component for Simulation.
The SAS software component which is used in creating SAS simulation is called SAS Simulation Studio. Its graphical user interface provides a full set of tools for building, executing, and analyzing the results of discrete event simulation models.
Different types of statistical distributions on which SAS simulation can be appped is psted below.
SIMULATE DATA FROM A CONTINUOUS DISTRIBUTION
SIMULATE DATA FROM A DISCRETE DISTRIBUTION
SIMULATE DATA FROM A MIXTURE OF DISTRIBUTIONS
SIMULATE DATA FROM A COMPLEX DISTRIBUTION
SIMULATE DATA FROM A MULTIVARIATE DISTRIBUTION
APPROXIMATE A SAMPLING DISTRIBUTION
ASSESS REGRESSION ESTIMATES