SAS Base and Advance

SAS (previously “Statistical Analysis System”) is a software suite developed by SAS Institute for advanced analytics, multivariate analysis, business intelligence, data management, and predictive analytics. SAS was developed at North Carolina State University from 1966 until 1976, when SAS Institute was incorporated. SAS is an expensive commercial software and is mostly used by large corporations with huge budgets.

Despite the insurgence of tremendous competition SAS remains to feature one of the most trusted and most used programming languages as far as advanced analytics and data science are concerned. It is important for us to notice that SAS has been in the market as a leading language for about two decades. This shows that how adaptable and plastic it has been throughout the time in an industry that is characterized by change and development. The knowledge of SAS can lead you to the very niche of advanced analytics and data science.

Main Features

  • Gain an understanding of SAS GUI, library statements, importing and exporting of data and variable attributes
  • Learn and perform data exploration techniques using proc print, proc summary, proc contents and more
  • Learn SAS functions and procedures for data manipulation using the Data Step
  • Combine dataset methods, understand select statements and joins in SQL
  • Understand the power of SAS Macros and how they can be used for faster data manipulation
  • Reduce the amount of regular SAS codes required for analytics using Macros
  • Learn the various techniques for combining and modifying datasets like concatenation, one-to-one merging and many-to-one merging
  • Master the various PROC statements used for analytics including PROC UNIVARIATE, PROC MEANS, PROC FREQ, PROC CORP, and more

Introduction to SAS

1
What is SAS?
2
User interface of various SAS products: SAS 9.2
3
Concept of Permanent and Temporary Libraries
4
Introduction to Key Concepts on SAS Data Sets
5
Data Comprehension
6
Types of variables in SAS
7
Creating temporary and permanent SAS data sets
8
Introduction to Metadata Structures of a data set: INFORMATS, FORMATS, LENGTH, LABEL, RENAME statements
9
Copying SAS data sets from one library to another library

Subsetting of Data

1
Creating subsets of a data set using FIRSTOBS, OBS, KEEP, DROP
2
Creating Data Sets and Variables based on conditionality
3
Use of Where, If and When conditional statements to create subsets
4
Use of And, Or, In, Contains logical operators and the sign of inequalities
5
Introduction to IF Then Do Else Then Do
6
Separate out data sets using SAS conditional statements
7
Import various type of data sets like Text files (.txt, .csv), Excel files (.xls) etc using SAS codes
8
Export SAS data sets into different type of file like Text files (.txt, .csv), Excel files (.xls) etc
9
Generate HTML, RTF and PDF reports outside SAS environment using ODS statement
10
Generating listing reports using Print Procedure
11
VAR statement in Print Procedure
12
Suppressing observation column in Print Procedure
13
Getting the number of observation in the output
14
Using custom labels in Print Procedure
15
Using Arithmetic operators like SUM

Generating listing and summary reports using Report Procedure

1
The Report Window and NOWINDOWS option
2
Using Column Statement
3
Using DEFINE Statement to define a variable as DISPLAY, ORDER, GROUP, ANALYSIS, ACROSS variable
4
Creating new columns runtime
5
Customizing the output by changing WIDTH, FORMAT, etc for a column

Accessing the Metadata report using Contents Procedure

1
Descriptor portion and data portion of a data set
2
Creating descriptor portion using Contents procedure
3
Use of options like NODS, _ALL_, POSITION, SHORT

Generate Frequency Distribution using Frequency Procedure

1
Concept of Frequency Distribution using TABLE statement
2
Descriptive statistics of numeric variables using MEANS, SUMMARY, UNIVARIATE
3
Use of Summary Statistics, like Mean, Median, etc

Miscellaneous Topics

1
Creating formats using Format Procedure
2
Use of Transpose Procedure to manipulate SAS datasets
3
Enhance the quality of the reports through the use of labels
4
SAS Formats, titles and various default reporting options

SAS Functions

1
SAS date Functions to manipulate date variables in a data set
2
SAS functions to manipulate Character and Numeric data
3
SAS functions to convert character data to numeric data and vice versa

Combining SAS Datasets

1
Appending SAS datasets using data step and Append procedure
2
Sort observations in SAS datasets in the specified order of magnitude, Nodupkey and Nodup
3
Merging two or more datasets in data step

Reading Raw Data Sets

1
Use of INFILE statement options when reading raw data file
2
Use of various components for reading raw data files
3
Reading Different type of Inputs (list Column and Formatted Inputs)
4
Reading missing values by using MISSOVER, DSD option and Truncover

Array in SAS

1
Process SAS data sets using Do loops and Array
2
Do loop statements in SAS data step
3
Concept and use of Array in SAS
4
Dimension of an Array and Array elements
5
Introduction to Temporary array and the use of it
6
Multi Dimensional Arrays

Debugging Techniques in SAS

1
Using debugger window
2
Reading the log window
3
Creating Accumulated Variables

Structured Query Language (SQL) in SAS using Proc SQL

1
Introduction to Structured Query Language in SAS
2
Advantages of using Proc SQL over Traditional SAS Codes
3
Creating new variables using Proc SQL
4
Use of select statement to display Column headings from a table
5
Creating outputs and new tables using Proc SQL statement
6
Selecting Duplicate/unique values
7
Use of Calculated option, label, format option in Proc SQL
8
Query for sorting a report and Data sets in a specified order of magnitude
9
Compare solving a problem using the SQL procedure versus using traditional SAS programming techniques
10
Use of Customised formula for Calculations and creating subsets of the data sets
11
Using other conditional operators like Between – And, Contains, Missing, Like
12
Use of Case expression on Select statement
13
Application of Where clause, Having Clause
14
Construct sub queries within a PROC SQL step Combining Queries with Set Operators
15
Introduction to SQL Joins and a comparison between SAS merge and SQL join
16
Use of Inner Join, Left Join, Right Join, Full join
17
Creating and updating tables using Proc SQL
18
Editing observations and Data table management
19
Updating Data Values, deleting rows, Altering columns, deleting a table using Proc SQL

SAS Macros

1
Getting started with Macro facility
2
Introduction to SAS programs and Macro Processing
3
Generating SAS Codes with Macro Language
4
Defining and Calling Macros
5
Introduction to Macro parameters and the concept of Positional and Keyword parameters
6
Introduction to Macro Variables and the Concept of Global and Local Macro variables
7
Defining Arithmetic and Logical expressions in SAS Macro
8
Evaluation of Arithmetic and Logical expressions in SAS Macro
9
Macro functions
10
Introduction to Storing and Reusing Macros
11
Creating Macro in Data Step
12
Creating macro variables with Proc SQL
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Enrolled: 34 students
Duration: 48 hours
Lectures: 89
Video: 96 hours
Level: Intermediate

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