Book contents
- Frontmatter
- Contents
- Preface
- Acknowledgments
- 1 Introduction
- 2 Principles of Statistics
- 3 Introduction to Linear Regression
- 4 Assessing the Regression
- 5 Multiple Linear Regression
- 6 Indicators, Interactions, and Transformations
- 7 Nonparametric Statistics
- 8 Logistic Regression
- 9 Diagnostics for Logistic Regression
- 10 Poisson Regression
- 11 Survival Analysis
- 12 Proportional Hazards Regression
- 13 Review of Methods
- Appendix: Statistical Tables
- References
- Selected Solutions and Hints
- Index
1 - Introduction
Published online by Cambridge University Press: 05 June 2012
- Frontmatter
- Contents
- Preface
- Acknowledgments
- 1 Introduction
- 2 Principles of Statistics
- 3 Introduction to Linear Regression
- 4 Assessing the Regression
- 5 Multiple Linear Regression
- 6 Indicators, Interactions, and Transformations
- 7 Nonparametric Statistics
- 8 Logistic Regression
- 9 Diagnostics for Logistic Regression
- 10 Poisson Regression
- 11 Survival Analysis
- 12 Proportional Hazards Regression
- 13 Review of Methods
- Appendix: Statistical Tables
- References
- Selected Solutions and Hints
- Index
Summary
We are surrounded by data. With a tap at a computer keyboard, we have access to more than we could possibly absorb in a lifetime. But is this data the same as information? How do we get from numbers to understanding? How do we identify simplifying trends – but also find exceptions to the rule? The computers that provide access to the data also provide the tools to answer these questions. Unfortunately, owning a hammer does not enable us to build a fine house. It takes experience using the tools, knowing when they are appropriate, and also knowing their limitations.
The study of statistics provides the tools to create understanding out of raw data. Expertise comes with experience, of course. We need equal amounts of theory (in the form of statistical tools), technical skills (at the computer), and critical analysis (identifying the limitations of various methods for each setting). A lack of one of these cannot be made up by the other two.
This chapter provides a review of statistics in general, along with the mathematical and statistical prerequisites that will be used in subsequent chapters. Even more broadly, the reader will be reminded of the larger picture. It is very easy to learn many statistical methods only to lose sight of the point of it all.
What Is Statistics?
In an effort to present a lot of mathematical formulas, we sometimes lose track of the central idea of the discipline.
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- Information
- Applied Linear Models with SAS , pp. 1 - 20Publisher: Cambridge University PressPrint publication year: 2010