SAS for Elementary Statistics: Getting Started provides an introduction to SAS programming for those who have experience with introductory statistical methods. It is also an excellent programming supplement for an introductory statistics course. It is appropriate for the beginning programmer with no
SAS system for elementary statistical analysis
โ Scribed by Sandra Schlotzhauer, Ramon Littell
- Publisher
- SAS Institute
- Year
- 1997
- Tongue
- English
- Leaves
- 457
- Edition
- 2nd ed
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
This updated edition shows how to use the SAS System to perform basic statistical analysis. General topics include creating a data set with the SAS System; summarizing data with descriptive statistics, frequency tables, and bar charts; comparing groups (t-tests, one-way ANOVA, and nonparametric analogues); performing basic linear regression (lines, curves, and two-variable models); performing simple regression diagnostics (residuals plots, studentized residuals); and creating and analyzing tables of data. Using real-life examples, this beginner's guide bridges the gap between statistics texts and SAS documentation.
Supports releases 6.07 and higher of SAS software.
๐ SIMILAR VOLUMES
If you need to get one book to get you through an introductory statistics course, which uses SAS, grab this. The topics, from importing and doing descriptive statistics out to the inferential statistics that are typically taught in a one quarter stat class are well covered with a nice mixture of te
<p>A beginning text especially designed for those who probably will not go in to statistics professionally but who plan to go into the physical, biological, and social sciences. The material presupposes only one semester of elementary mathematical analysis.</p> <p>Originally published in 1948.</p> <
<p><P>This book is an integrated treatment of applied statistical methods, presented at an intermediate level, and the SAS programming language. It serves as an advanced introduction to SAS as well as how to use SAS for the analysis of data arising from many different experimental and observational
<span>This book is intended for use as the textbook in a second course in applied statistics that covers topics in multiple regression and analysis of variance at an intermediate level. Generally, students enrolled in such courses are p- marily graduate majors or advanced undergraduate students from