DURATION | PRICE | inc-VAT | |
---|---|---|---|
2 | £600 | £720 | |
This online Learning Pathway will provide you with a fundamental knowledge and understanding of the essential elements of the programming language of SAS. There are mini quizzes and comprehensive exercises throughout to help assess and reinforce your learning. Summary Learning Objectives: By the end of this pathway you will be able to: 1. Explain the introductory elements and concepts of the Language of SAS. 2. Describe the fundamental Programming Concepts within the Language of SAS. Please read our Terms and Conditions and our Privacy Policy. Duration: 10-12 hours (plus additional time for exercises) |
WHAT YOU'LL BE TAUGHT...
INTRODUCTION TO SAS PROGRAMMING (eMODULE)
Learning Objective: Explain what the Language of SAS is used for and by whom.
• Explanation about SAS and who uses it
• Data Access
• Data Management
• Data Analysis
• Data Presentation
BASIC CONCEPTS (eMODULE)
Learning Objective: Explain how the Language of SAS is used to access, manage, analyse and present data.
• What is a dataset, a database and a relational database?
• Libraries, LIBREFS, LIBNAME statement
• Referencing a dataset
• The Data Step procedure
• Basic Procedures including PROC MEANS and PROC PRINT
INVESTIGATING SAS DATASETS (eMODULES)
Learning Objective: Define how to investigate datasets in the Language of SAS using two types of Procedure.
• The PRINT procedure
• Metadata, the CONTENTS procedure
• Types of data
PROGRAMMING CONCEPTS (eMODULE)
Learning Objective: Describe the key programming concepts within the Language of SAS.
• Program components – Data Steps and Procedures
• Programming language is made up of statements, expressions, functions & call routines, options, formats, and informats
• Managing Syntax errors
• Naming conventions
DATA STEP PROCESSING (eMODULE)
Learning Objective: Explain how the two phases of Data Step Processing work to create new datasets and variables.
• Data Step syntax: The DATA and SET Statements
• Creating Datasets
• Creating Variables
• Data Step processing, i.e. what goes on in the background when you submit your data step code.
Selecting Variables and Observations (eModule)
Learning Objective: Define Variables and Observations to be read from and written to datasets.
• KEEPing and DROPing Variables
• The IF Statement
• The WHERE Statement
• FIRSTOBS= and OBS=
• IS NULL or IS MISSING
• BETWEEN-AND
• CONTAINS (?) and SOUNDS LIKE (=*)
Introduction to Functions (online class)
Learning Objective: Describe how functions are used to transform Numeric, Date and Character values.
• SUM and MEAN functions for numerics
• TODAY(), MDY, DAY, WEEKDAY, WEEK, MONTH, QTR and YEAR
• UPCASE, LOWCASE and SUBSTR functions for character values
IF THEN ELSE Processing (online class)
Learning Objective: Apply conditional logic to assign values to variables and to control which observations are written to multiple output datasets.
• IF-THEN-ELSE syntax
• DO-END syntax
• The LENGTH statement
• The OUTPUT statement
• The DELETE statement
System Formats (online class)
Learning Objective: Describe how formats can be used to change the displayed values of Character, Numeric and Date variables.
• System supplied formats
• $w. simple character
• w.d, COMMAw.d, NLMNYw.d numeric and currency formats
• DATEw. and DDMMYYw. date formats
Sorting data with PROC SORT (online class)
Learning Objective: Use the Sort Procedure to re-order observations in a dataset, remove duplicate data and create an output dataset.
• PROC SORT syntax
• Using BY and NODUPKEY to remove duplicates
• The OUT= option
Combining Datasets VERTICALLY (online class)
Learning Objective: Explain the three methods which can be used to combine datasets together vertically.
• Concatenate multiple datasets
• Append one dataset to another
• Interleave multiple datasets
Combining Datasets HORIZONTALLY (online class)
Learning Objective: Describe how datasets can be combined together horizontally or merged including matches and non-matches.
• One-to-One merging
• Match merging
• One-to-Many merging
• Selecting matches and non-matches
• Introduction to Proc SQL joins
Frequency Counts with PROC FREQ (online class)
Learning Objective: Use the Freq Procedure to generate frequency counts and percentages of data values within a dataset.
• One-way frequencies
• Two-way frequencies
• Create an output dataset
Summary Statistics with PROC MEANS (online class)
Learning Objective: Use the Means Procedure to calculate summary statistics within a dataset, selecting classification and analysis variables.
• PROC MEANS syntax
• CLASS and VAR statements
• Specifying Statistic keywords
• Create an output dataset
Summary Tables with PROC TABULATE (online class)
Learning Objective: Use the Tabulate Procedure to calculate summary statistics in one, two and three dimension tabular form.
• PROC TABULATE syntax
• CLASS and VAR statements
• Define table content – TABLE statement
• Produce multiple output tables
Analysing Values with PROC UNIVARIATE (online class)
Learning Objective: Describe the 5 default statistical tables produced by the Univariate Procedure and the options available to modify the output.
• PROC UNIVARIATE syntax
• CLASS and VAR statements
• ID statement and Options
List Reports with PROC PRINT (online class)
Learning Objective: Create customised list reports with the Print Procedure.
• Select variables and observations
• Creating and using variable labels
• Adding titles and footnotes
• Grouping observations
• Calculating totals and sub-totals
Reading from and writing to Non-SAS Files (online class)
Learning Objective: Explain three methods which can be used to read from or write to non-SAS Files including delimited raw data and Excel files.
• Using Data Step syntax to read and write raw data
• Access Excel workbooks using the XLSX engine
• Creating output files with Proc Export
Error handling and Debugging (online class)
Learning Objective: Writing and running SAS programs is often not successful on the first attempt so it’s important to be able to read and understand Log messages.
• NOTES, WARNINGS and ERRORS
• Making sense of common error messages
• Methods for finding and correcting errors
• Testing your code
• Debugging your code
WHAT YOU SHOULD ALREADY KNOW...
Pre-requisites:
This learning pathway is aimed at those who are new to the Language of SAS.
You should already have:
• Knowledge of your computer system
• Basic computer literacy
• Some previous programming experience, although this is not essential
For the hands-on practice activities in the course, you will need access to an environment that runs the programming Language of SAS. On our courses, we signpost you to some of the free tools available.
Check out the options below to review system requirements:
• WPS Community Edition - Windows
• WPS Community Edition - macOS
• SAS® OnDemand for Academics - Web Editor