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 REG

We will take this example forward and test the significance of the variables in a regression model:

Data Build Validation;
Set Model;
If Date lt '01Dec2017'd then output Build;
Else output Validation;
Run;

PROC REG DATA=build plots=diagnostics(unpack);
ID date;
MODEL stock = basket_index -- m1_money_supply_index;
RUN;

The observations that have been used have decreased in the regression model. Previously, in the correlation procedure, we had 594 rows of data, which has now decreased to 564. We have called the new data the build data. The last 30 observations in the data have been left out of the model building process and have been put in a dataset called validation:

In the Analysis of Variance (ANOVA) table, the eight degrees of freedom refers to the eight independent variables that are available to estimate the parameters of predicting the dependent variable. Total...