Book Image

Hands-On SAS for Data Analysis

By : Harish Gulati
Book Image

Hands-On SAS for Data Analysis

By: Harish Gulati

Overview of this book

SAS is one of the leading enterprise tools in the world today when it comes to data management and analysis. It enables the fast and easy processing of data and helps you gain valuable business insights for effective decision-making. This book will serve as a comprehensive guide that will prepare you for the SAS certification exam. After a quick overview of the SAS architecture and components, the book will take you through the different approaches to importing and reading data from different sources using SAS. You will then cover SAS Base and 4GL, understanding data management and analysis, along with exploring SAS functions for data manipulation and transformation. Next, you'll discover SQL procedures and get up to speed on creating and validating queries. In the concluding chapters, you'll learn all about data visualization, right from creating bar charts and sample geographic maps through to assigning patterns and formats. In addition to this, the book will focus on macro programming and its advanced aspects. By the end of this book, you will be well versed in SAS programming and have the skills you need to easily handle and manage your data-related problems in SAS.
Table of Contents (17 chapters)
Free Chapter
1
Section 1: SAS Basics
4
Section 2: Merging, Optimizing, and Descriptive Statistics
7
Section 3: Advanced Programming
10
Section 4: SQL in SAS
13
Section 5: Data Visualization and Reporting

Proc Univariate

This is a procedure that can accomplish many tasks. However, it is frequently used for producing descriptive statistics based on moments (including skewness and kurtosis), quantiles or percentiles, frequency tables, and extreme values. It can produce a host of charts and goodness of fit tests for a lot of distribution types.

Since the previous function dealt with frequency tables, let's kick-start learning about this procedure by producing something similar. Use the following code to produce the frequency table:

ODS Select Frequencies;
Proc Univariate Data = Analyse Freq;
Var _All_;
Run;

This will result in the following output:

As you can see, we can produce frequencies using Proc Univariate. However, if frequencies are the main analysis goal, try and use Proc Freq. If you omit the ODS Select option at the top of the query, you will get a detailed output...