SAS programming
Data

SAS programming

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About the Course

Course Code: Stat1002

Duration: 24 hours

weekend: 2 days (14 hours)

weekday Evening: 1  week (10 hours)

Time: 6:30 pm – 8:30 pm

 

 

SAS Programming Description

This 24 hours introductory SAS course is the most practical and comprehensive introduction to the many facets of SAS concepts and applications you’ll find anywhere.

As a participant, you will get a thorough briefing in the nuts and bolts of data analysis by using SAS.

This qualification is primarily aimed towards:

  • Those who require a basic understanding of the SAS;
  • Those who need understanding of how SAS can be used to enhance the quality of data analysis;
  • Data scientists or others working within an organization that has adopted and adapted SAS who need to be informed about, or contribute to an ongoing service improvement.

 

Course Outline

Module 1 – Overview of foundation SAS

  • Describe the functionality of Foundation SAS.
  • Describe the structure and design of Foundation SAS.

Module 2– Getting started with SAS

  • Introduction to SAS Programs
  • Submitting a SAS Program

Module 3– Working with SAS Syntax

  • Mastering Fundamental Concepts
  • Diagnosing and Correcting Syntax Errors

Module 4 – Getting Familiar with SAS Data Sets

  • Accessing SAS Data Libraries
  • Accessing Relational Databases

Module 5 – Reading SAS Data Sets

  • Introduction to Reading Data
  • Using SAS Data as Input
  • Subsetting Observations and Variables
  • Adding Permanent Attributes

Module 6 – Reading Excel Worksheets

  • Using Excel Data as Input
  • Doing More with Excel Worksheets (Self-Study)

Module 7 – Reading Delimited Raw Data Files

  • Using Standard Delimited Data as Input
  • Using Nonstandard Delimited Data as Input

Module 8 – Validating and Cleaning Data

  • Introduction to Validating and Cleaning Data
  • Examining Data Errors When Reading Raw Data Files
  • Validating Data with the PRINT and FREQ Procedures
  • Validating Data with the MEANS and UNIVARIATE Procedures

Module 9 – Manipulating Data

  • Creating Variables
  • Creating Variables Conditionally
  • Subsetting Observations

Module 10 – Combining SAS Data Sets

  • Introduction to Combining Data Sets
  • Appending a Data Set
  • Concatenating Data Sets
  • Merging Data Sets One-to-One
  • Merging Data Sets One-to-Many
  • Merging Data Sets with Non-Matches

Module 11 – Enhancing Reports

  • Using Global Statements
  • Adding Labels and Formats
  • Creating User-Defined Formats
  • Subsetting and Grouping Observations
  • Directing Output to External Files

Module 12 – Producing Summary Reports

  • Using the FREQ Procedure
  • Using the MEANS Procedure
  • Using the TABULATE Procedure

Module 13 – Introduction to Graphics Using SAS/GRAPH

  • Introduction
  • Creating Bar and Pie Charts
  • Creating Plots
  • Enhancing Output

Module 14 – Controlling Input and Output

  • Outputting Multiple Observations
  • Writing to Multiple SAS Data Sets
  • Selecting Variables and Observations

Module 15 – Summarizing Data

  • Creating an Accumulating Total Variable
  • Accumulating Totals for a Group of Data

Module 16 – Reading Raw Data Files

  • Reading Raw Data Files with Formatted Input
  • Controlling When a Record Loads
  • Additional Techniques for List Input (Self-Study)

Module 17 – Data Transformations

  • Introduction
  • Manipulating Character Values (Part 1)
  • Manipulating Character Values (Part 2)
  • Manipulating Numeric Values
  • Converting Variable Type

Module 18 – Debugging Techniques

  • Using the PUTLOG Statement
  • Using the DEBUG Option

Module 19 – Processing Data Iteratively

  • DO Loop Processing
  • SAS Array Processing
  • Using SAS Arrays

Module 20 – Restructuring a Data Set

  • Rotating with the DATA Step
  • Using the TRANSPOSE Procedure

Module 21 – Combining SAS Data Sets

  • Using Data Manipulation Techniques with Match-Merging

Who will benefit most ?

  • The SAS qualification is open to any individuals who may have an interest in the subject and enable the holders of the qualification to apply the SAS practices for advanced data analysis without further guidance.

 

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I would have no hesitation in recommending you to my friends.

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