Statistical Analysis System (SAS) Skill Overview
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- Category: Technical > Business intelligence and data analysis
Description
SAS, or Statistical Analysis System, is a software suite used for advanced analytics, business intelligence, data management, and predictive analytics. It provides a graphical point-and-click user interface for non-technical users and more advanced options through the SAS language. SAS skills range from understanding basic software functions and syntax to writing complex programs and performing intricate statistical analyses. As proficiency increases, users can automate tasks, optimize code performance, handle large datasets, and integrate SAS with other technologies. Mastery of SAS can lead to the development and implementation of sophisticated data solutions, making it a valuable skill in various industries.
Expected Behaviors
Micro Skills
Understanding of the SAS Explorer window
Proficiency in using the SAS Editor window
Familiarity with the SAS Results window
Understanding of SAS libraries
Familiarity with SAS datasets
Proficiency in using SAS procedures
Proficiency in using the SAS toolbar
Familiarity with SAS menus
Knowledge of DATA and PROC steps
Familiarity with INPUT and SET statements
Proficiency in using assignment statements
Knowledge of SAS statements
Understanding of SAS operators
Knowledge of SAS data types
Understanding of SAS variable naming rules
Understanding of the PDV (Program Data Vector)
Ability to use the OUTPUT statement
Understanding of conditional processing
Ability to use loops
Understanding of PROC PRINT
Ability to use PROC SORT
Understanding of PROC MEANS
Ability to use PROC FREQ
Ability to create new variables
Understanding of variable transformations
Ability to modify existing variables
Understanding of how to handle missing values
Knowledge of SELECT statement
Understanding of JOIN operations
Ability to perform subqueries
Understanding of how to use SQL functions
Knowledge of arithmetic operations
Understanding of conditional transformations
Knowledge of handling missing data
Knowledge of MERGE statement
Understanding of SET statement
Knowledge of macro variables and macro functions
Ability to create and call macros
Understanding of how to use macro loops
Understanding of regression analysis
Knowledge of ANOVA and other variance analysis techniques
Ability to perform multivariate analysis
Understanding of survival analysis
Knowledge of basic graph types
Knowledge of advanced graph types
Creating macros
Calling macros
Regression analysis
ANOVA
Efficient data step coding
Efficient PROC SQL coding
Data step processing
Familiarity with the layout and components
Ability to navigate through the interface
Understanding of the project creation process
Ability to manage projects
Understanding of the task concept
Ability to use wizards
Understanding of the code creation process
Ability to execute code
Ability to use snippets
Tech Experts

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