Master SAS for data analysis, data management, and regression.
Key Features
- Master SQL procedures such as combining datasets, different join types, and select Statements, and understand the need for macro variables
- Learn about statistics and data analytics techniques using SAS Data Science tools
- Apply advanced statistical concepts such as clustering, linear regression, and decision trees to solve real-world business problems
Book Description
SAS is one of the most popular applications for data analysis and is used widely in enterprises across various sectors such as finance, and healthcare. It holds the highest job market share of all analytics tools available today. If you have a basic SAS programming background and want to get into Data Analysis by mastering SAS and taking your skills to a different level, then this is the right course for you!
This course will help you become proficient in using SAS to handle data, build models, and analyze data so you can gain powerful insights quickly and easily. You will start with a quick refresher of basic SAS and then explore advanced statistical concepts (such as clustering and linear/logistic regression), decision trees, and time series analysis in-depth in SAS. You will also master SAS macros, PROC SQL procedures, and advanced SAS procedures so you can use SQL queries to manage and manipulate your data efficiently.
By the end of this video, you will be an expert in SAS programming and will have taken your skills to the next level. Also, you will be able to handle and manage your data-related problems very easily in SAS and build statistical models.
All the code and supporting files for this course are available on GitHub at
https://github.com/PacktPublishing/Mastering-SAS-Programming-Videos
What you will learn
- Gain an understanding of basic SAS, its GUI, libraries, and importing/exporting data
- Use PROC SQL to fetch data from multiple tables by using JOINS
- Explore the power of SAS macros and optimize code and for faster data manipulation
- Gain an in-depth understanding of statistics in SAS to summarize and graph data and also draw inferences from it
- Perform cluster analysis on a dataset by applying K-means clustering to understand the purpose of unsupervised Machine Learning in SAS
- Build a decision-tree model to visually and explicitly represent decisions and decision making
- Apply linear or logistic regression in SAS and build models for predictive analytics on sales data
- Build a time series model to see patterns in data
- Use ARIMA modeling to build a model and make forecasts
Who this book is for
If you are a professional statistician or analyst with exposure to the basics of SAS programming and want to be an expert, this course is for you. Experienced SAS professionals who want to harness data science with SAS will also benefit from this course.
Requirements: Basic understanding of SAS programming
