Introduction to SAS
• What is SAS?
• SAS User Interface
• User interface
• Active Data sets
• Introduction to SAS Libraries and SAS
Introduction to key concepts on SAS Data Sets and Data Comprehension
• Types of variables in SAS
• Creating temporary and permanent SAS data sets
• Introduction to INFORMATS, FORMATS, LENGTH, LABEL, RENAME statements
• Copying SAS data sets from one library to another library
• Creating subsets of a data set using FIRSTOBS, OBS, KEEP, DROP
Creating Data Sets and Variables based on conditionality.
• Use of Where, If and When conditional statements to create subsets from a data set.
• Use of And, Or, In, Contains logical operators and the sign of inequalities.
• Separate out data sets based on suitable conditions using SAS conditional statements
Import and Export data sets using SAS
• Import various type of data sets like Text files (.txt, .csv), Excel files (.xls) Etc. using SAS Codes.
• Import data sets using the SAS Import Wizard.
• Export SAS data sets into different type of file like Text files (.txt, .csv), Excel files (.xls) Etc.
• Generate HTML, RTF and PDF reports outside SAS environment using ODS statement.
Generating Different Reports Using SAS Pro
• Generate listing reports using Print and Report procedures.
• Descriptor portion and data portion of a data set
• Creating descriptor portion using Contents procedure and use of keywords like nods, _all_, position, short.
• Generate Summary reports and frequency Distribution using FREQ procedure.
• Descriptive statistics of numeric variables using MEANS, SUMMARY, UNIVARIATE and TABULATE procedure.
• Creating formats using Format Procedure.
• Use of Transpose procedure to manipulate SAS data sets.
• Enhance the quality of the reports through the use of labels, SAS Formats, titles, footnotes and various default reporting options.
SAS Functions to manipulate SAS Data Sets and Variables
• Appending two or more SAS data sets using data step and Append procedure.
• Sort observations in SAS data sets in the specified order of magnitude, Nodupkey and Nodup
• Merging two or more data sets in data step.
Combining SAS Data Sets
• SAS date Functions to manipulate date variables in a data set.
• Use of SAS functions to manipulate Character and Numeric data.
• SAS functions to convert character data to numeric data and vice versa.
Reading Raw Data Sets
• Use of INFILE statement options when reading raw data file
• Use of various components like line pointer controls, trailing @ controls for reading raw data files.
• Reading missing values by using MISSOVER, DSD option and PAD option while reading raw files.
Process SAS data sets using do loops and Array
• Do loop statements in SAS data step Concept of SAS Array and use of Array in SAS
• Dimension of an Array, Array elements, introduction to temporary array and the use of it.
• Identify and resolve programming and logic errors
• Recognizing and correcting SAS Syntax Errors
Structured Query Language (SQL) in SAS (using Proc SQL)
• Introduction to Structured Query Language in SAS.
• Advantages of using Proc SQL over Traditional SAS Codes
• Creating new variables using Proc SQL.
• Use of select statement to display Column headings from a table.
• Creating outputs and new tables using Proc SQL statement.
• Selecting Duplicate/unique values.
• Use of Calculated option, label, format option in Proc SQL.
• Writing query for sorting a report and Data sets in a specified order of magnitude.
• Remerging, remerging for totals.
• Compare solving a problem using the SQL procedure versus using traditional SAS Programming techniques.
• Use of Customized formula for Calculations and creating subsets of the data sets.
• Using other conditional operators like Between – And, Contains, Missing, Like.
• Use of Case expression on Select statement.
• Application of Where clause, Having Clause.
• Construct sub queries within a PROC SQL step Combining Queries with Set Operators.
• Introduction to SQL Joins and a comparison between SAS merge and SQL join.
• Use of Inner Join, Left Join, Right Join, Full join.
• Creating and updating tables using Proc SQL.
• Editing observations and Data table management like Updating Data Values, deleting rows, Altering columns, deleting a table, in a Table using Proc SQL.
• Creating macro variables with Proc SQL.
• Getting started with Macro facility
• Introduction to SAS programs and Macro Processing
• Generating SAS Codes with Macro Language
• Defining and Calling Macros
• Introduction to Macro parameters and the concept of Positional and Keyword parameters.
• Introduction to Macro Variables and the Concept of Global and Local Macro variables.
• Defining Arithmetic and Logical expressions in SAS Macro.
• Evaluation of Arithmetic and Logical expressions in SAS Macro.
• Macro functions.
• Interfaces with the SQL Procedure.
• Introduction to Storing and Reusing Macros
• Writing Efficient Macro
SAS Predictive models with Live Business case studies across different
• Steps in building Regression Model with Business case studies.
o assumptions regarding linear regression
o examine data prior to modeling
o creating the model
o testing for assumption validation
o writing the equation
o testing for multicollinearity
o testing for auto correlation
o testing for effects of outliers
o testing the fit
• Annova Model
• Ancova model
• Arima Model
• Factor Analysis
• Cluster Analysis
• Demo Exam of all the models in respect to case studies