Mastering SAS Programming

Video description

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.

What You Will Learn

  • Gain an understanding of basic SAS, its GUI, libraries, and importing/exporting data
  • Use PROC SQL to fetch data from multiple tables by using JOINS
  • Explore the power of SAS macros and optimize code and for faster data manipulation
  • Gain an in-depth understanding of statistics in SAS to summarize and graph data and also draw inferences from it
  • Perform cluster analysis on a dataset by applying K-means clustering to understand the purpose of unsupervised Machine Learning in SAS
  • Build a decision-tree model to visually and explicitly represent decisions and decision making
  • Apply linear or logistic regression in SAS and build models for predictive analytics on sales data
  • Build a time series model to see patterns in data
  • Use ARIMA modeling to build a model and make forecasts


If you are a professional statistician or analyst with exposure to the basics of SAS programming and want to be an expert, this course is for you. Experienced SAS professionals who want to harness data science with SAS will also benefit from this course.

Requirements: Basic understanding of SAS programming

About The Author

Ekta Saraogi: Ekta Saraogi has been a computer engineer for the past 12 years. She started her career as a Java developer. One thing that has always intrigued her is the power of data to drives business outcomes by the right tools.

She ventured into the field of data science to get the best out of her technical and business experience and drove and delivered cost-effective business analytics solutions for global businesses.

She is now a freelancer, a corporate/online trainer, and a mentor in data science with SAS, R, and Python. She is working on various projects across different domains for global clients across the US and UK. She is also the author of the 'SAS in Practice' video course Published by Packt.

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Table of contents

  1. Chapter 1 : Quick Refresher to Base SAS
    1. The Course Overview
    2. What is Business Analytics?
    3. Analytical Tools and Advantages of SAS
    4. SAS Libraries and Importing/Exporting Data
    5. Combining and Merging Datasets
    6. Data Manipulation
  2. Chapter 2 : Accessing Data Using SQL
    1. Introducing SQL
    2. Retrieving Data from Single Table
    3. Retrieving Data from Multiple Tables
    4. PROC SQL Views
  3. Chapter 3 : SAS Macros, Functions, and Programs
    1. Introducing Macros
    2. Macro Variables
    3. Creating Automatic and User-Defined Macro Variables
    4. Macro Functions
    5. Macro Programs
    6. Macros with SQL
  4. Chapter 4 : Statistics in SAS
    1. Introduction to Statistics
    2. Statistical Terms
    3. Types of Variables
    4. Hypothesis Testing
    5. Parametric and Non Parametric Tests
    6. Procedures in SAS for Descriptive Statistics
  5. Chapter 5 : Performing Cluster Analysis and Decision Trees
    1. Introduction to Cluster
    3. PROC CLUSTER Example
    4. K-Means Clustering
    5. Decision Trees
  6. Chapter 6 : Performing Linear and Logistic Regression
    1. Introduction to Regression
    2. Linear Regression
    3. Linear Regression Example
    4. Logistic Regression
  7. Chapter 7 : Working with Time Series Data
    1. Need for Time Series Analysis
    2. PROC TIMESERIES with E-Commerce Dataset
    3. Time Series - Options
    4. Time Series Patterns
    5. ARIMA Model
    6. ARIMA Model - Demo
  8. Chapter 8 : Factor Analysis and Creating Custom Graphs
    1. Introduction to Principal Factor Analysis
    2. Principal Factor Analysis: Kaiser's MSA and Factor Extraction
    3. Creating Scatterplots and Line Graphs Using GPLOT
    4. Creating Charts and Boxplots Using PROC GCHART and PROC BOXPLOT

Product information

  • Title: Mastering SAS Programming
  • Author(s): Ekta Saraogi
  • Release date: May 2020
  • Publisher(s): Packt Publishing
  • ISBN: 9781788291248