Elementary Statistics for Geographers, Third Edition

Name: Elementary Statistics for Geographers, Third Edition
Availability: InStock
ISBN: 9781572304840

ISBN-10: 1572304847

ISBN-13: 9781572304840

Edition: 3rd 2009 (Revised)

Authors: Lawrence A. Pervin, Oliver P. John, Gerald M. Barber, David L. Rigby, James E. Burt

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Book details

List price: $99.00
Edition: 3rd
Copyright year: 2009
Publisher: Guilford Publications
Publication date: 3/19/2009
Binding: Hardcover
Pages: 653
Size: 6.50" wide x 9.25" long x 1.25" tall
Weight: 2.574
Language: English

Lawrence A. Pervin is Professor of Psychology at Rutgers University. Following an undergraduate education at Brooklyn College and Queens College (City University of New York), he obtained his doctorate from Harvard University in 1962. After six years at Princeton University he went to Rutgers as an Associate Dean to help develop a new, experimental college. The author of many journal articles, including a Citation Classic, and invited book chapters, he also is the author of two leading personality texts, «MDUL»Personality: Theory and Research«MDNM» (Fifth Edition) and «MDUL»Current Controversies and Issues in Personality«MDNM» (Second Edition). Dr.…

(UPDATED BY KL, 10/21/03) James E. Burt is Professor of Geography at the University of Wisconsin/n-/Madison. Gerald M. Barber currently teaches in the Department of Geography at Queen's University in Canada and maintains an independent consulting practice.

James E. Burt is Professor and former chair of Geography at the University of Wisconsin-Madison. His current research focuses on development of expert system and statistical approaches for quantitative prediction of soils information. nbsp; Gerald M. Barber is Associate Professor of Geography and teaches introductory and advanced courses in statistics at Queen’s University in Kingston, Ontario, Canada.nbsp;In addition, he is the director of the program in Geographic Information Science and runs the GISLAB. His principal interests are in the application of statistical and optimization models within GIS.David L. Rigby is Professor of Geography and Statistics at the University of…




Introduction



Statistics and Geography



Statistical Analysis and Geography



Data



Measurement Evaluation



Data and Information



Summary



Descriptive Statistics



Displaying and Interpreting Data



Displaying and Interpretation of the Distributions of Qualitative Variables



Display and Interpretation of the Distributions of Quantitative Variables



Displaying and Interpreting Time-Series Data



Displaying and Interpreting Spatial Data



Summary



Describing Data with Statistics



Measures of Central Tendency



Measures of Dispersion



Higher Order Moments or Other Numerical Measures of the Characteristics of Distributions



Using Descriptive Statistics with Time-Series Data



Descriptive Statistics for Spatial Data



Summary



Review of Sigma Notation



An Iterative Algorithm for Determining the Weighted or Unweighted Euclidean Median



Statistical Relationships



Relationships and Dependence



Looking for Relationships in Graphs and Tables



Introduction to Correlation



Introduction to Regression



Temporal Autocorrelation



Summary



Review of the Elementary Geometry of a Line



Least Squares Solution via Elementary Calculus



Inferential Statistics



Random Variables and Probability Distributions



Elementary Probability Theory



Concept of a Random Variable



Discrete Probability Distribution Models



Continuous Probability Distribution Models



Bivariate Random Variables



Summary



Counting Rules for Computing Probabilities



Expected Value and Variance of a Continuous Random Variable



Sampling



Why Do We Sample?



Steps in the Sampling Process



Types of Samples



Random Sampling and Related Probability Designs



Sampling Distributions



Geographic Sampling



Summary



Point and Interval Estimation



Statistical Estimation Procedures



Point Estimation



Interval Estimation



Sample Size Determination



Summary



One-Sample Hypothesis Testing



Key Steps in Classical Hypothesis Testing



prob-value Method of Hypothesis Testing



Hypothesis Tests Concerning the Population Mean m and p<$$$>



Relationship between Hypothesis Testing and Confidence Interval Estimation



Statistical Significance versus Practical Significance



Summary



Two-Sample Hypothesis Testing



Difference of Means



Difference of Means for Paired Observations



Difference of Proportions



The Equality of Variances



Summary



Nonparametric Methods



Comparison of Parametric and Nonparametric Tests



One- and Two-Sample Tests



Multisample Kruskal-Wallis Test



Goodness-of-Fit Tests



Contingency Tables



Estimating a Probability Distribution: Kernel Estimates



Bootstrapping



Summary



Analysis of Variance



The One-Factor, Completely Randomized Design



The Two-Factor, Completely Randomized Design



Multiple Comparisons Using the Scheffe Contrast



Assumptions of the Analysis of Variance



Summary



Derivation of Equation 11-11 from Equation 11-10



Inferential Aspects of Linear Regression



Overview of the Steps in a Regression Analysis



Assumptions of the Simple Linear Regression Model



Inferences in Regression Analysis



Graphical Diagnostics for the Linear Regression Model



Summary



Extending Regression Analysis



Multiple Regression Analysis



Variable Transformations and the Shape of the Regression Function



Validating a Regression Model



Summary



Patterns in Space and Time



Spatial Patterns and Relationships



Point Pattern Analysis



Spatial Autocorrelation



Local Indicators of Spatial Association



Regression Models with Spatially Autocorrelated Data



Geographically Weighted Regression



Summary



Time Series Analysis



Time Series Processes



Properties of Stochastic Processes



Types of Stochastic Processes



Removing Trends: Transformations to Stationarity



Model Identification



Model Fitting



Times Series Models, Running Means, and Filters



The Frequency Approach



Filter Design



Summary


Appendix: Statistical Tables


Index


About the Authors