SAS Fundamentals Course Outline
Overview
Do you want to create data analysis reports without writing a line of code? This course introduces SAS programming using SAS Studio. The power of SAS Studio comes from its visual point-and-click user interface that generates SAS code. All that you will learn in this course, you can apply seamlessly using SAS Enterprise Guide or SAS Viya as all platforms use the same programming language and same syntax.
It is easier to learn SAS than to learn R and Python to accomplish data cleaning, statistics, and visualization tasks. If you use any other SAS product, this course will cover the SAS programming syntax and fundamentals needed to do your data reports.
The course provides real-life examples including analyzing election predictions, stocks, oil and gold prices, crime, marketing, and healthcare. You will see data science in action and how easy it is to perform complicated tasks and visualizations in SAS.
You will learn, step-by-step, how to do visualizations, including maps. In most cases, you will not need a line of code as you work with the SAS graphical user interface. The course includes explanations of the code that SAS IDE generates automatically. You will learn how to edit this code to perform more complicated advanced tasks.
You will:
• Become familiar with SAS IDE
• Understand essential visualizations
• Know the fundamental statistical analysis required in most data science and analytics reports
• Clean the most common data set problems
• Use linear progression for data prediction
• Write programs in SAS
Intended Audience
This class is most appropriate for data scientists and those wanting data analytics. Individuals mastering the content of this class will be qualified to pass the SAS certification exams for SAS 9.4 Base Programming (A00-231) and SAS 9.4 Programming Fundamentals (A00-215). Also, class participants will be on their way toward being qualified for the SAS 9.4 Advanced Programming (A00-212). Speak with the instructor or to a customer service representative to get additional supplemental material to prepare for the Advanced Programming certification.
Prerequisites
No prior knowledge of SAS is required.
Number of Days
3 days
COURSE OUTLINE
Part I: Basics
Data Science in Action
Data Science Process
Case Study: Presidential Elections in Maine
Population
Gender
Race
Age
Voter Turnout
Winning Candidates in 2012
Categories/Issues
Factors Affecting Maine’s Economy
Modeling
My 2016 Predictions
My 2020 Predictions
Getting Started
How Do You Install SAS Studio?
What Is SAS and SAS Studio?
Tour
Tasks
Reports
Graphs
Snippets
Main Components of a SAS Program
Data Step
Variable Types
Proc Step
Libraries
Accessing Your Existing Local Files
Accessing Data in SAS Libraries
Create a New Library
Add a New Table to the Library
INFILE technique
Data Visualization
Scatter Plot
Scatter Plot Code
Scatter Plot Relationships
Plotting More Than One Scatter Plot in the Same Image
Histogram
Appearance Tab
Series Plot
Bar Chart
How Do You Sort A Bar Chart?
Create a Histogram Using a Bar Chart
Bubble Chart
Maps
Bubble Map
Cluster Analysis
Statistical Analysis and Linear Models
Statistical Analysis
One-Way Frequency
Summary Statistics
Correlation Analysis
T-Tests
One-Sample T-tests
Paired-sample T-test
Two-Sample T-tests
Linear Models
One-Way ANOVA
N-Way ANOVA
Advanced Data Preprocessing and Feature Engineering
Comment Statement
Arithmetic Operators
How to Represent Missing Values in Raw Data
Comparison Operators
PROC SQL Statement
SELECT-WHERE Statement
WHERE Clause
SELECT-WHEN-OTHERWISE Statement
DO Loops
Preparing Data for Analysis
Label
Format
Create New Variables
Rearrange the Dataset Variables
IF Statement
IF (Condition) Without THEN statement
IF-THEN Statement
IF-THEN-ELSE Statement
DROP Statement
SET Statement
Regression
Simple Linear Regression
Multiple Linear Regression
Logistic Regression
Project/Case Study
We will work on another data set to practice by hand everything we learned throughout the course. We will clean the data column by column including character, numeric, date and time variables and how to do typecasting. We will find the correlation between the outcome and the variables.
View outline in Word
XSAS01
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