SAS for R Users

SAS for R Users

by Ajay Ohri
Released September 2019
Publisher(s): Wiley
ISBN: 9781119256410

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Book description

 BRIDGES THE GAP BETWEEN SAS AND R, ALLOWING USERS TRAINED IN ONE LANGUAGE TO EASILY LEARN THE OTHER

SAS and R are widely-used, very different software environments. Prized for its statistical and graphical tools, R is an open-source programming language that is popular with statisticians and data miners who develop statistical software and analyze data. SAS (Statistical Analysis System) is the leading corporate software in analytics thanks to its faster data handling and smaller learning curve. SAS for R Users enables entry-level data scientists to take advantage of the best aspects of both tools by providing a cross-functional framework for users who already know R but may need to work with SAS.

Those with knowledge of both R and SAS are of far greater value to employers, particularly in corporate settings. Using a clear, step-by-step approach, this book presents an analytics workflow that mirrors that of the everyday data scientist. This up-to-date guide is compatible with the latest R packages as well as SAS University Edition. Useful for anyone seeking employment in data science, this book:

  • Instructs both practitioners and students fluent in one language seeking to learn the other
  • Provides command-by-command translations of R to SAS and SAS to R
  • Offers examples and applications in both R and SAS
  • Presents step-by-step guidance on workflows, color illustrations, sample code, chapter quizzes, and more
  • Includes sections on advanced methods and applications

Designed for professionals, researchers, and students, SAS for R Users is a valuable resource for those with some knowledge of coding and basic statistics who wish to enter the realm of data science and business analytics.

AJAY OHRI is the founder of analytics startup Decisionstats.com. His research interests include spreading open source analytics, analyzing social media manipulation with mechanism design, simpler interfaces to cloud computing, investigating climate change, and knowledge flows. He currently advises startups in analytics off shoring, analytics services, and analytics. He is the author of Python for R Users: A Data Science Approach (Wiley), R for Business Analytics, and R for Cloud Computing.

Table of contents

  1. Cover
  2. Preface
  3. Scope
  4. 1 About SAS and R
    1. 1.1 About SAS
    2. 1.2 About R
    3. 1.3 Notable Points in SAS and R Languages
    4. 1.4 Some Important Functions with Comparative Comparisons Respectively
    5. 1.5 Summary
    6. 1.6 Quiz Questions
    7. Quiz Answers
  5. 2 Data Input, Import and Print
    1. 2.1 Importing Data
    2. 2.2 Importing Data in SAS
    3. 2.3 Importing Data in R
    4. 2.4 Providing Data Input
    5. 2.5 Data Input in SAS
    6. 2.6 Printing Data
    7. 2.7 Summary
    8. 2.8 Quiz Questions
    9. Quiz Answers
  6. 3 Data Inspection and Cleaning
    1. 3.1 Introduction
    2. 3.2 Data Inspection
    3. 3.3 Missing Values
    4. 3.4 Data Cleaning
    5. 3.5 Quiz Questions
    6. Quiz Answers
  7. 4 Handling Dates, Strings, Numbers
    1. 4.1 Working with Numeric Data
    2. 4.2 Working with Date Data
    3. 4.3 Handling Strings Data
    4. 4.4 Quiz Questions
    5. Quiz Answers
  8. 5 Numerical Summary and Groupby Analysis
    1. 5.1 Numerical Summary and Groupby Analysis
    2. 5.2 Numerical Summary and Groupby Analysis in SAS
    3. 5.3 Numerical Summary and Group by Analysis in R
    4. 5.4 Quiz Questions
    5. Quiz Answers
  9. 6 Frequency Distributions and Cross Tabulations
    1. 6.1 Frequency Distributions in SAS
    2. 6.2 Frequency Distributions in R
  10. 7 Using SQL with SAS and R
    1. 7.1 What is SQL?
    2. 7.2 SQL Select
    3. 7.3 Merges
    4. 7.4 Summary
    5. 7.5 Quiz Questions
    6. Quiz Answers
  11. 8 Functions, Loops, Arrays, Macros
    1. 8.1 Functions
    2. 8.2 Loops
    3. 8.3 Arrays
    4. 8.4 Macros
    5. 8.5 Quiz Questions
    6. Quiz Answers
  12. 9 Data Visualization
    1. 9.1 Importance of Data Visualization
    2. 9.2 Data Visualization in SAS
    3. 9.3 Data Visualization in R
    4. 9.4 Quiz Questions
    5. Quiz Answers
  13. 10 Data Output
    1. 10.1 Data Output in SAS
    2. 10.2 Data Output in R
    3. 10.3 Quiz Questions
    4. Quiz Answers
  14. 11 Statistics for Data Scientists
    1. 11.1 Types of Variables
    2. 11.2 Statistical Methods for Data Analysis
    3. 11.3 Distributions
    4. 11.4 Descriptive Statistics
    5. 11.5 Inferential Statistics
    6. 11.6 Algorithms in Data Science
    7. 11.7 Quiz Questions
    8. Quiz Answers
  15. Further Reading
  16. Index
  17. End User License Agreement

Product information

  • Title: SAS for R Users
  • Author(s): Ajay Ohri
  • Release date: September 2019
  • Publisher(s): Wiley
  • ISBN: 9781119256410