Complete Practical SAS, Statistics Data Analysis Course
- Development
- May 02, 2025

Complete & Practical SAS, Statistics & Data Analysis Course, available at $79.99, has an average rating of 4.2, with 171 lectures, based on 1767 reviews, and has 11280 subscribers.
You will learn about Be equipped with a powerful tool for the most sexy data analytics career path! Read and write various types of raw data with different formats and options Create and modify various professional and statistical reports Be aware of statistical analysis and concepts such as non parametric test, interaction, correlation.. Master the most complete SAS graphics tool such GTL and statistical plots Learn comprehensive SAS Macro programming knowledge variables and user defined functions Perform many real world case studies retail banks, credit bureau, marketing firms and clinical trials Apply powerful data manipulation SQL, subsetting, slicing, filtering, transformation, ranking, sorting.. Understand data management and data piping Use SAS ODS help deliver many useful objects such as charts, tables between different systems Hundreds of SAS sample codes to explain arrays, functions and business cases This course is ideal for individuals who are Beginners or job seekers interested in learning SAS Programming, statistical and data analysis in industry fields. or People who wish to enter data science/analytics field. It is particularly useful for Beginners or job seekers interested in learning SAS Programming, statistical and data analysis in industry fields. or People who wish to enter data science/analytics field.
Enroll now: Complete & Practical SAS, Statistics & Data Analysis Course
Summary
Title: Complete & Practical SAS, Statistics & Data Analysis Course
Price: $79.99
Average Rating: 4.2
Number of Lectures: 171
Number of Published Lectures: 171
Number of Curriculum Items: 171
Number of Published Curriculum Objects: 171
Original Price: $79.99
Quality Status: approved
Status: Live
What You Will Learn
Who Should Attend
Target Audiences
You should take this course!?
? If you need a complete and comprehensive package that covers SAS programming, intuitive statistics interpretation, data analysis, and predictive modeling, and
? If you would like to learn by doing various practical use cases fitting in the positions in different business portfolios, and
? Whether you are a job seeker or beginner intending to start a data science career
Then this around?18 hours course is right for you!
This complete SAS course includes more than 150?lectures and contains 11 real world case studies/projects in different applied areas such as banking and marketing. After this intensive training, you will be equipped with a powerful tool for the most sexy data analytics career path!
Course Curriculum
Chapter 1: Introduction
Lecture 1: What are you going to learn from this course
Chapter 2: SAS environment and basic concepts
Lecture 1: Introduce SAS environment
Lecture 2: SAS library
Lecture 3: Try SAS codes
Lecture 4: Home work and data installation
Lecture 5: SAS Cloud Version
Lecture 6: Introduction to SAS Studio Installation on University Edition
Chapter 3: Get started SAS programming
Lecture 1: Create data sets from external files
Lecture 2: SAS program – create data sets
Lecture 3: Valid names and comments
Lecture 4: SAS program Valid names and comments
Lecture 5: Data type and format
Lecture 6: SAS program data type and format
Lecture 7: SAS program – date and format
Lecture 8: Mechanism of SAS data set
Lecture 9: Summarize SAS operations
Chapter 4: Input and output raw data
Lecture 1: List input (1)
Lecture 2: List input (2)
Lecture 3: SAS program list input
Lecture 4: Read data with fixed layout
Lecture 5: Read data with modified list input
Lecture 6: Input data with other features
Lecture 7: Write data using data step
Lecture 8: SAS program –write data
Lecture 9: Import and export data
Chapter 5: Manipulate data by data step programming
Lecture 1: Duplicate data sets
Lecture 2: SAS program duplicate data sets
Lecture 3: Modify variables
Lecture 4: SAS program modify variables
Lecture 5: Variables selection.
Lecture 6: Rename variables
Lecture 7: SAS program rename variables
Lecture 8: Assign labels to variables
Lecture 9: SAS program assign labels to variables
Lecture 10: Subsetting data sets
Lecture 11: SAS program Subsetting data sets
Chapter 6: Control flow in SAS
Lecture 1: Structured programming (I)
Lecture 2: SAS program Structured programming (I)
Lecture 3: Structured programming (II)
Lecture 4: SAS program Structured programming (II)
Chapter 7: SAS data step functions
Lecture 1: Data step character functions
Lecture 2: SAS program –data step character functions
Lecture 3: Data step numeric functions
Lecture 4: SAS program numeric functions
Lecture 5: Data step special functions
Lecture 6: Data step special functions
Lecture 7: User defined format
Lecture 8: SAS program User defined format
Chapter 8: Use cases study (1)
Lecture 1: Case study 001(read employee data)
Lecture 2: SAS program read employee data
Lecture 3: Case study 002(read chronic disease data)
Lecture 4: SAS program Case study 002(read chronic disease data)
Lecture 5: Case study 003 ( read business account data)
Lecture 6: SAS program Case study 003 ( read business account data)
Lecture 7: Case study 004 (process stock data)
Lecture 8: SAS program Case study 004 (process stock data)
Chapter 9: Other SAS features in data step programming
Lecture 1: Automatic Variables(_N_ and _ERROR_)
Lecture 2: Output statement
Lecture 3: Return statement
Lecture 4: pinpoint the first and last record
Lecture 5: SAS program Pinpoint the first and last record
Lecture 6: Retain statement
Lecture 7: SAS program Retain statement
Lecture 8: Data step array (1)
Lecture 9: Data step array (2)
Chapter 10: Use cases study (2)
Lecture 1: Case study 005(create new KPI features)
Lecture 2: Case study 006(students grades)
Chapter 11: Browse, sort and combine data
Lecture 1: Browse and print data set
Lecture 2: SAS program Browse and print data set
Lecture 3: Sort data
Lecture 4: SAS program sort data
Lecture 5: Merge multiple data sets
Lecture 6: Stack data sets
Lecture 7: Examples of merging and splitting data sets
Chapter 12: Data processing and analysis
Lecture 1: Transpose data sets
Lecture 2: Examples of transposing data
Lecture 3: Understand statistics and distribution..
Lecture 4: Summarize continuous data
Lecture 5: Examples of PROC MEANS (1)
Lecture 6: Examples of PROC MEANS (2)
Lecture 7: Examples of PROC MEANS (3)
Lecture 8: Summarize categorical variables
Lecture 9: Examples of PROC FREQ (1)
Lecture 10: Examples of PROC FREQ (2)
Lecture 11: Examples of PROC FREQ (3)
Lecture 12: Understand uni-variate study
Lecture 13: Examples of uni-variate analysis
Lecture 14: Ranking data and bucket analysis
Instructors

Shenggang Li
Senior Data Scientist
Rating Distribution
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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