Master Data Analysis Using SAS Programming

In this module, we will guide you through setting up SAS Studio/SAS OnDemand for Academics, ensuring you are familiar with essential tools and configurations. You'll also explore the WPS platform.

In this module, we will focus on importing different file formats such as .txt, .csv, and .xlsx into SAS. You'll learn how to effectively use the proc import feature.

In this module, we will explore the essential building blocks of SAS syntax, focusing on how the data step and proc step serve different functions.

In this module, we will dive into advanced data manipulation techniques using SAS, exploring dataset options, delimiters, and methods for reading dates in data.

In this module, we will revisit importing techniques, focusing on how to import an SPSS file into SAS.

In this module, we will cover the basics of input types and informats, showing you how to read and manage different data structures.

In this module, we will delve into the use of arrays in SAS. You'll learn how to recode and construct new variables using arrays.

In this module, we will explore a range of SAS functions that are essential for data processing, including RAND, LENGTH, and COMPRESS functions.

In this module, we will focus on advanced SAS programming techniques, particularly how to vertically combine raw data files.

In this module, we will focus on creating visual representations of data, such as scatter plots and bar graphs.

In this module, we will focus on statistical analysis using SAS, covering T-tests and Chi-Square tests.

In this module, we will dive into regression analysis, covering both linear and multiple regression.

In this module, we will apply the knowledge gained throughout the course in healthcare-related case studies.

In this module, we will introduce the fundamentals of SQL in SAS, covering syntax and basic queries.

In this module, we will cover how to join datasets using SAS SQL, including inner, left, right, and full joins.

In this module, we will explore how to work with tables using SAS SQL, including creation and modification.

In this module, we will focus on practical applications of SAS SQL, including table comparison and duplicate identification.

In this module, we will cover the fundamentals of SAS indexes, focusing on optimization and management.

In this module, we will explore the fundamentals of SAS macros, focusing on creation and implementation.

In this module, we will introduce predictive modeling using logistic regression in SAS.

In this module, we will focus on the preliminary steps of building a predictive model.

In this module, we will cover advanced data preparation techniques for predictive modeling.

In this module, we will explore the key evaluation metrics for predictive models.

In this final module, we will address the top five most commonly asked questions about SAS certification.