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About This Book
Statistics Analysis of Geographical Data: An Introduction provides a comprehensive and accessible introduction to the theory and practice of statistical analysis in geography. It covers a wide range of topics including graphical and numerical description of datasets, probability, calculation of confidence intervals, hypothesis testing, collection and analysis of data using analysis of variance and linear regression. Taking a clear and logical approach, this book examines real problems with real data from the geographical literature in order to illustrate the important role that statistics play in geographical investigations. Presented in a clear and accessible manner the book includes recent, relevant examples, designed to enhance the reader's understanding.
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1
Dealing with data
STUDY OBJECTIVES
- Understand the nature and purpose of statistical analysis in geography.
- View statistical analysis as a means of thinking critically with quantitative information.
- Distinguish between the different types of geographical data and their uses and limitations.
- Understand the nature of measurement error and the need to account for error when making quantitative statements.
- Distinguish between accuracy and precision and to understand how to report the precision of geographical measurements.
- Appreciate the methodological limitations of statistical data analysis.
1.1 The role of statistics in geography
1.1.1 Why do geographers need to use statistics?
We know in the next 20 years the world population will increase to something like 8.3 billion people.Sir John Beddington, UK Government Chief Scientist12010 hits global temperature high.BBC News, 20th January 20112
- to describe and measure the things that you observe;
- to characterize measurement error in your observations;
- to test hypotheses and theories;
- to predict and explain the relationships between variables.
1.2 About this book
1.3 Data and measurement error
1.3.1 Types of geographical data: nominal, ordinal, interval, and ratio
Table of contents
- Cover
- Title Page
- Table of Contents
- Preface
- 1 Dealing with data
- 2 Collecting and summarizing data
- 3 Probability and sampling distributions
- 4 Estimating parameters with confidence intervals
- 5 Comparing datasets
- 6 Comparing distributions
- 7 Analysis of variance
- 8 Correlation
- 9 Linear regression
- 10 Spatial Statistics
- 11 Time series analysis
- Appendix A: Introduction to the R package
- Appendix B: Statistical tables
- References
- Index
- End User License Agreement