Complete SAS Programming Guide - Learn SAS and Become a Data Ninja

Complete SAS Programming Guide - Learn SAS and Become a Data Ninja

by Ermin Dedic
Released December 2022
Publisher(s): Packt Publishing
ISBN: 9781837633531

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Video description

SAS programming continues to be the language of choice for most enterprises/corporations. In 2018, 92% of Fortune 100 companies used SAS. It is the go-to for many industries, including banking/finance, insurance, healthcare, pharmaceutical, and automotive.

The first part of the course utilizes the Data Step; the second part looks at SAS SQL, and the third part looks at Macro Programming/Programs. The author has added a section on SAS predictive modeling using logistic regression. Here, we will build a SAS Model. In other words, we will build a predictive model (also known as predictive analytics) while following critical principles to ensure we get things right.

This course is also developed to help you become SAS Certified Specialist: Base Programming certified.

By the end of this course, you will learn how to code in the SAS programming language, to help you start a career/gain employment, or move up at your current company. If you are studying SAS at a post-secondary institution, this course can not only help you with school projects but prepare you for a career after you complete your education.

Disclaimer: This course uses a commercial license from WPS.

Learning SAS programming means that you will be able to accomplish the same goal on any software that supports the SAS language. The author personally uses WPS.

What You Will Learn

  • Discover the data step, the primary way to program in SAS
  • Learn about the proc step that is utilized for more particular tasks
  • Apply SAS SQL, the SAS interpretation of SQL
  • Look at the practical application of SAS SQL
  • Learn the fundamentals of Macro facility
  • Look at SAS predictive modeling and evaluation metrics

Audience

This course is designed for the users of the SAS Enterprise Guide, as being able to code inside of EG is the next natural step and skill to obtain. Individuals that are considering a career or want to gain employment with the biggest corporations/enterprises out there along with the ones looking to become SAS Certified Specialist: Base Programming will gain a lot from this course. The students new to SAS syntax and or looking for a refresher will learn and enjoy this course thoroughly.

No prior programming knowledge is required to take this course but only a stable internet connection.

About The Author

Ermin Dedic: Ermin Dedic started his studies by studying psychology for six years. He received his bachelor’s degree from the University of Ottawa, Canada, and his master’s degree from the University of Calgary, Canada. Ermin also spent two years in a master’s program (school/child psychology) at the University of Calgary before voluntarily withdrawing, in part to focus more on his teaching. It was through academia that he was introduced to and fell in love with statistics and statistical programming with SAS.

He is passionate about making education accessible and fun for students. Ermin believes that students learn better when they feel the passion that the instructor has for the content.

Table of contents

  1. Chapter 1 : Introduction to the Course
    1. SAS Studio/SAS OnDemand for Academics – Register, Upload, Run Code
    2. WPS – How to Find, Install, Register for, Use, and Upload Datasets
    3. Common Problems with Install/Upload (Watch for Best Course Experience!)
  2. Chapter 2 : Importing
    1. Import .txt
    2. Import .csv
    3. Import .XLSX
  3. Chapter 3 : SAS Syntax, Data Step Versus Proc Step, SAS Compared to R/Python
    1. Data Step Versus Proc Step
    2. SAS Syntax
    3. Manually Creating Data with R, Python, and SAS
  4. Chapter 4 : Working with Data
    1. Data Set Options
    2. What If Your Data Is Separated by a Dot or Something Else? (Delimiters)
    3. Reading Data Instream in Data Step (Typing Data Right into Coding Area)
    4. Reading DATES in Data
    5. Creating Variables/Calculations
    6. More on Creating New Variables
    7. Automatic Variables
    8. Filtering Observations (So Only Some Data Shows Up)
    9. Intuition for If-Then/Else and Do, Do-While, Do-Until
    10. If-Then Conditional Logic
    11. DO Iterative Loop and Variations (DO WHILE, DO Until)
    12. More on DO Group Processing (Without Index/Counter Variable)
    13. More on the WHERE Expression/Statement
    14. Sorting Observations (PROC SORT and BY Statements)
    15. Merging Two Datasets
    16. Using SET Statement to Merge
    17. Data Reduction and Cleaning Your Data
    18. LENGTH Statement
    19. Creating a Counting (Enumeration) Variable
  5. Chapter 5 : Back to Importing
    1. Importing SPSS File with SAS Language
  6. Chapter 6 : Input Types and Informats + User-Defined Formats
    1. List Input
    2. Column Input
    3. Formatted Input and Informats
    4. User-Defined Formats
  7. Chapter 7 : Arrays
    1. Arrays 1 (Recoding Variables)
    2. Arrays 2 (Constructing New Variables)
  8. Chapter 8 : SAS Functions
    1. Understanding SAS Functions
    2. RAND Function (Producing a Sample with Distribution of Your Choice)
    3. LENGTH, LENGTHN, LENGTHC Functions (Are You Working with a Large Dataset?)
    4. TRIM Function (Want to Get Rid of Trailing Blanks?)
    5. COMPRESS Function (Remove Characters from String, and All Types of Blanks)
    6. Input and Put Functions
    7. CATX Function
    8. SCAN Function
    9. Coalesce Function
    10. Verify Function
    11. Substr Function
  9. Chapter 9 : Advanced Techniques – Flexibilities and Efficiency
    1. Flexible Programming 1 - Combining multiple raw data files vertically
  10. Chapter 10 : Visual Representation of Data
    1. Scatter Plot
    2. Bar Graph
  11. Chapter 11 : Statistical Analysis
    1. T-Test Independent Samples Overview (Example)
    2. Doing an Independent Samples T-Test Analysis
    3. Chi-Square Independence Overview (Example)
    4. Doing a Chi-Square (Independent Groups) Analysis
  12. Chapter 12 : Statistical Analysis – Part 2 (Linear and Multiple Regression)
    1. Refresh Your Memory - Regression Edition
    2. Performing the Linear Regression
    3. Performing Multiple Regression
  13. Chapter 13 : Case Studies
    1. Case Study (HealthCare Case Study) - Part 1
    2. Case Study (HealthCare Case Study) - Part 2
    3. Congrats on Finishing Part 1: Data Step
  14. Chapter 14 : SQL Fundamentals
    1. SQL Syntax
    2. WHERE Clause
    3. SELECT Statement and Columns
    4. CASE Logic
    5. Summary Functions
  15. Chapter 15 : SAS SQL and Joining
    1. How to Perform an Inner Join
    2. How to Join Three Tables
    3. How to Perform a Left/Right Join
    4. How to Perform a Full Join
  16. Chapter 16 : Working with Tables Using SAS SQL
    1. How to Create a Table Using SAS SQL
    2. Altering Columns (Add, Modify, Delete, Add Values to Column)
    3. Inserting Rows with a Query and Set Statement
  17. Chapter 17 : Practical Application of SAS SQL
    1. How to Compare Tables with SAS SQL
    2. Finding Duplicate Observations
    3. Customize the Way You Sort
    4. How to Update a Table Under Certain Conditions with SAS SQL
  18. Chapter 18 : Fundamentals of Utilizing SAS Indexes
    1. Intro to Indexes/Indices
    2. Should You Use an Index?
    3. Types of Indices
    4. Index Options
    5. Testing with Large Datasets
    6. Selecting Variable(s) for Your Index
    7. PROC Datasets and WHERE Expression
    8. BY Statement (Sorting Variables, While Exploiting Your Index)
    9. Handling Common Tasks with an Indexed Dataset
    10. Updating the Master Dataset with New Variables or Observations
  19. Chapter 19 : Macro Facility Fundamentals
    1. Types of Macro Variables
    2. Don't Lose Track of Your Macro Variables
    3. Macro Variable Assignment Rules
    4. Masking Special Characters
    5. Macro Functions (%Index and %Upcase)
    6. Macro Functions 2 (%Scan)
    7. Creating a Macro Variable (Helps You Modify Data Easier)
    8. Macro Programs Introduction
    9. Creating a Macro Example 1 (Greater Flexibility and Useful for Repetitive Coding)
    10. Creating a Macro Example 2 (Unique Sales Reports for Different Days)
    11. Creating a Macro Example 3 (Calculating Average Sales for Multiple Years)
    12. Debugging Options
    13. Storing Macros (External)
    14. Brainstorming for Logistic Macro Case Study
    15. Logistic Macro, Case Study – Part 1
    16. Logistic Macro, Case Study – Part 2
  20. Chapter 20 : Introduction to SAS Predictive Modeling Using Logistic Regression
    1. Business Applications of Predictive Modeling
    2. Analytics Challenges
    3. The Major Steps in Predictive Modeling
    4. Intuitive Understanding of Logistic Regression
  21. Chapter 21 : SAS Model – Predictive Modeling, Understanding the Problem and the Data
    1. Problem Statement/Hypothesis Generation
    2. Data Audit
    3. Univariate Analysis
    4. Bivariate Analysis
    5. Important Housekeeping
  22. Chapter 22 : SAS Predictive Modeling, Prepare the Input Variables
    1. Sources, Patterns, and Mechanisms of Missing Data
    2. Evaluating Missing Data Patterns with SAS
    3. 3 Phase Multiple Imputation Process Using SAS
    4. Considering the Output from PROC MI
    5. Oversampling and Adjusting for Oversampling
    6. Categorical Inputs
    7. Variable Clustering
    8. Multicollinearity
    9. Subset Selection
    10. Parameter Estimates
  23. Chapter 23 : SAS Predictive Modeling, Evaluation Metrics
    1. ROC Curve
    2. Scoring Validation Dataset Using Code
    3. Decile Calibration Plot
    4. Feature Engineering
  24. Chapter 24 : Extra Content
    1. Top Five SAS Certification Questions Answered

Product information

  • Title: Complete SAS Programming Guide - Learn SAS and Become a Data Ninja
  • Author(s): Ermin Dedic
  • Release date: December 2022
  • Publisher(s): Packt Publishing
  • ISBN: 9781837633531