A Handbook of Statistical Graphics Using SAS ODS
โ Scribed by Geoff Der (Author); Brian Everitt (Author)
- Publisher
- Chapman and Hall/CRC
- Year
- 2014
- Leaves
- 242
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
Easily Use SAS to Produce Your GraphicsDiagrams, plots, and other types of graphics are indispensable components in nearly all phases of statistical analysis, from the initial assessment of the data to the selection of appropriate statistical models to the diagnosis of the chosen models once they have been fitted to the data. Harnessing the full gr
โฆ Table of Contents
An Introduction to Graphics: Good Graphics, Bad Graphics, Catastrophic Graphics and Statistical Graphics. An Introduction to ODS Graphics. Graphs for Displaying the Characteristics of Univariate Data: Horse Racing, Mortality Rates, Forearm Lengths, Survival Times and Geyser Eruptions. Graphs for Displaying Cross-Classified Categorical Data: Germinating Seeds, Piston Rings, Hodgkin`s Disease and European Stereotypes. Graphs for Use When Applying t-Tests and Analyses of Variance: Skulls, Cancer Survival Times and Effect of Smoking on Performance. Linear Regression, the Scatterplot and Beyond: Galaxies, Anaerobic Threshold, Birds on Islands, Birth and Death Rates, U.S. Birth Rates during and after World War II, and Air Pollution in U.S. Cities. Graphs for Logistic Regression: Blood Screening, Women`s Role in Society and Feeding Alligators. Graphing Longitudinal Data: Glucose Tolerance Tests and Cognitive Behavioural Therapy (CBT) for Depression. Graphs for Survival Data: Motion Sickness and Breast Cancer. References. Index.
โฆ Subjects
Bioscience;Biology;Statistics for the Biological Sciences;Mathematics & Statistics;Statistics & Probability;Statistics;Statistical Computing;Statistical Theory & Methods
๐ SIMILAR VOLUMES
Describes usage of the Output Delivery System for statistical graphics in SAS/STAT 9.2.
The authors covered many topics in applied statistics, but they didn't mention anything about time series analysis. I am disappointed after reading this book. The biggest problem with this book is that it's overly simplistic - typically only one technique is illustrated for each topic - for example,
Powerful software often comes, unfortunately, with an overwhelming amount of documentation. As a leading statistics software package, SAS is no exception. Its manuals comprise well over 10,000 pages and can intimidate, or at least bewilder, all but the most experienced users.A Handbook of Statistica