Course Outline:
Introduction to SAS:
Overview of SAS and its applications
Installing and setting up SAS
Navigating the SAS environment (SAS Studio, SAS Enterprise Guide)
Basic SAS Programming:
Understanding the SAS programming language
Data steps and PROC steps
Reading and writing data
SAS syntax and basic commands
Data Management and Manipulation:
Importing and exporting data (CSV, Excel, databases)
Data cleaning and preprocessing
Sorting, merging, and concatenating datasets
Using formats and informats
Data Analysis and Reporting:
Descriptive statistics (mean, median, mode, standard deviation)
PROC FREQ, PROC MEANS, PROC UNIVARIATE
Generating summary reports
Creating and customizing tables and listings
Advanced Data Step Techniques:
Using arrays and loops
Conditional processing (IF-THEN-ELSE)
Combining data sets (MERGE, UPDATE, MODIFY)
Data step debugging techniques
SAS Functions and Expressions:
Numeric, character, date, and time functions
Creating and using custom functions
Applying functions for data transformation and analysis
Data Visualization:
Creating basic plots and charts (bar charts, histograms, scatter plots)
Customizing graphs (titles, labels, legends)
Advanced visualization techniques using SAS/GRAPH and ODS Graphics
Statistical Analysis:
Hypothesis testing
Analysis of variance (ANOVA)
Regression analysis (linear and logistic regression)
Time series analysis
Macro Programming:
Introduction to SAS macros
Writing and using macro variables and macro programs
Macro functions and debugging macros
Automating repetitive tasks with macros
SQL in SAS:
Introduction to PROC SQL
Performing queries and subqueries
Joining tables and data summarization
Using SQL within SAS programs
Advanced Analytics:
Predictive modeling (decision trees, random forests)
Machine learning techniques
Text analytics and natural language processing
Cluster analysis and principal component analysis
SAS Enterprise Guide:
Overview of SAS Enterprise Guide
Creating and managing projects
Using tasks and wizards for analysis
Automating processes and generating reports
SAS Visual Analytics:
Introduction to SAS Visual Analytics
Data exploration and visualization
Building interactive dashboards and reports
Sharing and collaboration features
Practical Applications and Case Studies:
Real-world examples and case studies
Practical exercises and projects
Best practices and tips for efficient programming
Skills Gained:
Proficiency in using SAS for data management, analysis, and reporting
Ability to write and debug SAS programs
Skills in data visualization and advanced statistical analysis
Competence in using SAS macros and PROC SQL for automation and complex queries
Knowledge of advanced analytics and machine learning techniques
Target Audience:
Data analysts
Statisticians
Business analysts
Researchers
Students and professionals in data-driven fields