SAS Programming Online Course
About the Course
SAS is one of the most popular applications for data analysis and is used widely in enterprises across various sectors such as finance, and healthcare. It holds the highest job market share of all analytics tools available today. If you have a basic SAS programming background and want to get into Data Analysis by mastering SAS and taking your skills to a different level, then this is the right course for you!
This course will help you become proficient in using SAS to handle data, build models, and analyze data so you can gain powerful insights quickly and easily. You will start with a quick refresher of basic SAS and then explore advanced statistical concepts (such as clustering and linear/logistic regression), decision trees, and time series analysis in-depth in SAS. You will also master SAS macros, PROC SQL procedures, and advanced SAS procedures so you can use SQL queries to manage and manipulate your data efficiently.
By the end of this video, you will be an expert in SAS programming and will have taken your skills to the next level. Also, you will be able to handle and manage your data-related problems very easily in SAS and build statistical models.
Course Curriculum
Quick Refresher to Base SAS
- The Course Overview
- What is Business Analytics?
- Analytical Tools and Advantages of SAS
- SAS Libraries and Importing/Exporting Data
- Combining and Merging Datasets
- Data Manipulation
Accessing Data Using SQL
- Introducing SQL
- Retrieving Data from Single Table
- Retrieving Data from Multiple Tables
- PROC SQL Views
SAS Macros, Functions, and Programs
- Introducing Macros
- Macro Variables
- Creating Automatic and User-Defined Macro Variables
- Macro Functions
- Macro Programs
- Macros with SQL
Statistics in SAS
- Introduction to Statistics
- Statistical Terms
- Types of Variables
- Hypothesis Testing
- Parametric and Non Parametric Tests
- Procedures in SAS for Descriptive Statistics
Performing Cluster Analysis and Decision Trees
- Introduction to Cluster
- PROC CLUSTER
- PROC CLUSTER Example
- K-Means Clustering
- Decision Trees
Performing Linear and Logistic Regression
- Introduction to Regression
- Linear Regression
- Linear Regression Example
- Logistic Regression
Working with Time Series Data
- Need for Time Series Analysis
- PROC TIMESERIES with E-Commerce Dataset
- Time Series - Options
- Time Series Patterns
- ARIMA Model
- ARIMA Model - Demo
Factor Analysis and Creating Custom Graphs
- Introduction to Principal Factor Analysis
- Principal Factor Analysis: Kaiser's MSA and Factor Extraction
- Creating Scatterplots and Line Graphs Using GPLOT
- Creating Charts and Boxplots Using PROC GCHART and PROC BOXPLOT
