What you'll learn:
- Learn SAS and be confident on your data analysis skills
- Learn to accomplish a task with various SAS techniques, with tons of examples and quizes
- Learn step-by-step statistical analysis from descriptive statistics, hypothesis testing to linear regression
- Learn data importing with different techniques for variuos type of data
- Use many important functions to make SAS programming easy
- Advanced concepts of meta data: formats and informats, labels, lengths, etc.
- Learn the manipulation techniques to prepare the data and make the data analysis-ready
- Perform dataset manipulations: subsetting, transposition, etc.
- Be able to properly interpret the results from statistical analyses
- I am giving out one course for free. Check out the last lecture after you enroll
COURSE ABSTRACT
This course aims to provide a comprehensive introduction to the SAS analytic software for Windows. Through a mixture of lectures and in-class examples, quizzes, and take-home assignments, students will gain experience using the SAS system for data manipulation, management and analysis. You will alsoexpect A LOT of extracurricularlearning materials forself-pacelearning, treat it as a BONUS!Emphasis will be placed on the skills and techniques necessary for efficient data manipulation, management and analysis. It is designed for students with little to no background with SAS, and an understanding of the basic statistical concepts. This will be anexcellentchoice for your first SASintroduction course for your data analysiscareer.
Plus, you will get a FREE course - SAS Data Issue Handling and Good Programming Practice (check out in the bonus lecture)!!!
WHAT DO I EXPECT?
A comprehensive course design from SAS basics to statistical analysis
Many in-class examples, exercises and take-home assignment
Master various techniques for dataimporting
Solid understanding of variable attributes, and learn variouscharacter/numericfunctions
IF-THEN/ELSE statements
Do loop and counter variables
Master DATA step with Concatenation, Merge,etc.
Exposed to several useful PROC step (PRINT, SORT, TRANSPOSE, etc.).
Descriptive statistics procedures (MEANS, UNIVARIATE, FREQ)
Hypothesis testing (UNIVARIATE, TTEST, ANOVA)
Correlations (CORR)
Regression (REG)
PREREQUISITE COURSES AND KNOWLEDGE:
No SAS background required;
Basic knowledge of statistics is preferred.
