Statistical Methods for Geography: A Student's Guide / Edition 4 available in Paperback
How do beginning students of statistics for geography learn to fully understand the key concepts and apply the principal techniques? This text, now in its Fourth Edition, provides exactly that resource. Accessibly written, and focussed on student learning, it’s a statistics 101 that includes definitions, examples, and exercise throughout.
Now fully integrated with online self-assessment exercises and video navigation, it explains everything required to get full credits for any undergraduate statistics module:
- Descriptive statistics, probability, inferential statistics, hypothesis testing and sampling, variance, correlation, regression analysis, spatial patterns, spatial data reduction using factor analysis and cluster analysis.
- Exercises in the text are complemented with online exercise and prompts that test the understanding of concepts and techniques, additional online exercises review understanding of the entire chapter, relating concepts and techniques.
- Completely revised and updated for accessibility, including new material (on measures of distance, statistical power, sample size selection, and basic probability) with related exercises and downloadable datasets.
It is the only text required for undergraduate modules in statistical analysis, statistical methods, and quantitative geography.
|Edition description:||Fourth Edition|
|Product dimensions:||9.00(w) x 7.30(h) x 1.00(d)|
About the Author
Peter A. Rogerson is SUNY (State University of New York) Distinguished Professor in the Department of Geography at the University at Buffalo, Buffalo, New York, USA. He also holds an adjunct appointment in the Department of Biostatistics and is a member of the National Center for Geographic Information and Analysis.
Table of ContentsIntroduction to Statistical Methods for GeographyDescriptive StatisticsProbability and Discrete Probability DistributionsContinuous Probability Distributions and Probability ModelsInferential Statistics: Confidence Intervals, Hypothesis Testing, and SamplingAnalysis of VarianceCorrelationIntroduction to Regression AnalysisMore on RegressionSpatial PatternsSome Spatial Aspects of Regression AnalysisData Reduction: Factor Analysis and Cluster AnalysisEpilogue