Statistical methods for geography: a student's guide
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
Los Angeles [u.a.]
SAGE
2015
|
| Ausgabe: | 4. ed. |
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027625826&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027625826&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| Umfang: | XVIII, 401 S. graph. Darst., Kt. |
| ISBN: | 9781446295724 9781446295731 |
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| 245 | 1 | 0 | |a Statistical methods for geography |b a student's guide |c Peter A. Rogerson |
| 250 | |a 4. ed. | ||
| 264 | 1 | |a Los Angeles [u.a.] |b SAGE |c 2015 | |
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| 650 | 4 | |a Geography |x Statistical methods | |
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Datensatz im Suchindex
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|---|---|
| adam_text | How do beginning students of statistics for geography learn to fully understand the by concepts and apply
the principal techniques?
Accessibly written and focussed on student learning, Statistical Methods for Geography is a statistics 101
that includes definitions, examples, and exercises throughout, Fully integrated with online self-assessment
exercises and video overviews, it explains everything required to get full credits for any undergraduate
statistics module.
• Coverage of descriptive statistics, probability, inferential statistics, hypothesis testing and sampling,
variance, correlation, regression analysis, spatial patterns, spatial data reduction using factor analysis
and cluster analysis
Both in-text and online exercises for every chapter, along with downloadable datasets
Video overviews of the principal ideas and learning outcomes in each chapter.
xm
About the Author
Preface
J XIV
Preface to the Second Edition
Preface to the Third Edition *W11
Preface to the Fourth Edition X1X
XX
About the Companion Website
xxi
1 INTRODUCTION TO STATISTICAL METHODS
FOR GEOGRAPHY
1.1 Introduction
1.2 The scientific method
1.3 Exploratory and confirmatory approaches in geography
1.4 Probability and statistics
1.4.1 Probability
1.4.2 Statistics
1.4.3 Probability paradoxes
1.4.4 Geographical applications of probability and statistics
1.5 Descriptive and inferential methods
1.6 The nature of statistical thinking
1.7 Special considerations for spatial data
1.7.1 The modifiable areal unit problem
1.7.2 Boundary problems
1.7.3 Spatial sampling procedures
1.7.4 Spatial autocorrelation
1.8 The structure of the book
1.9 Datasets
1.9.1 Introduction
1.9.2 Home sales in Milwaukee,Wisconsin, USA in 2012
Singapore census data for 2010
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Hypothetical UK housing prices
5 1990 Census Data for Erie County, New York
Di-$CRIPTI Vf: 5} AXIS TICS
2.1 Types of data
2.2 Visual descriptive methods
Measures of central tendency
2.4 Measures of variability
2.5 Other numerical measures for describing data
2: 5 i Coefficient of variation
2.5.2 Skewness
2.5.5 Kurtosis
2.5.4 Standard scores
$
2.4 Descriptive spatial statistics
2.6.1 The measurement of distance
2.6.2 Mean center
2.6.3 Median center
2.6.4 Standard distance
2.6.5 Relative distance
2.6.6 Illustration of spatial measures of central tendency and dispersion
2.6.7 Angular data
2.7 Descriptive statistics in SPSS 21 for Windows
2.7.1 Data input
2.7.2 Descriptive analysis
Solved exercises
Exercises
PROBABILITY AND DISCRETE PROBABILITY
DISTRIBUTIONS
3.1 Introduction
3.2 Sample spaces, random variables, and probabilities
3.5 Binomial processes and the binomial distribution
3.4 The geometric distribution
3.5 The Poisson distribution
3.6 The hypergeometric distribution
3.6.1 Application to residential segregation
3.6.2 Application to the space-time clustering of disease
3.7 Binomial tests in SPSS 21 for Windows
Solved exercises
Exercises
VII
4 CONTINUOUS PROB ~aU..U V i-O.AM
PROBABILITY Ivii •i x. - i
4 1 Introduction 90
,■) The uniform or rectangular distribution 91
4,3 The normal distribution 93
4 4 The exponential distribution 99
4 5 Summary of discrete and continuous distributions 104
4.6 Probability models 106
4 6, i The intervening opportunities model 106
4.6.2 A model of migration 111
4.6.3 The future of the human population 112
Solved exercises 113
Exercises 116
5 INFERENTIAL STATISTICS: CONFIDENCE INTERVALS.
HYPOTHESIS TESTING, AND SAMPLING 119
5.1 Introduction to inferential statistics 119
5.2 Confidence intervals 120
5.2.1 Confidence intervals for the mean 120
5.2.2 Confidence intervals for the mean when the sample size is small 122
5.2.3 Confidence intervals for the difference between two means 123
5.2.4 Confidence intervals for proportions 125
5.3 Hypothesis testing 126
5.3.1 Hypothesis testing and one-sample z-tests of the mean 126
5.3.2 One-sample f-tests 130
5.3.3 One-sample tests for proportions 133
5.3.4 Two-sample tests: differences in means 135
5.3.5 Two-sample tests: differences in proportions 139
5.3.6 Type II errors and statistical power 141
5.4 Distributions of the random variable and distributions of the test statistic 142
5.5 Spatial data and the implications of nonindependence 144
5.6 Further discussion of the effects of deviations from the assumptions 146
5.6.1 One-sample test of proportions: binomial distribution -
assumption of constant or equal success probabilities 146
5.6.2 One-sample test of proportions: binomial distribution -
assumption of independence 147
5.6.3 Two-sample difference of means test: assumption of independent
observations 149
5.6.4 Two-sample difference of means test: assumption of
homogeneity 151
viii
Sampling
Spatial sampling
Sample size considerations
Some tests for spatial measures of central tendency and
variability
: One-sample tests of means in SPSS 21 for Windows
5 V. S Interpretation
5 Two-sample ¿-tests in SPSS 21 for Windows
5.VU Data entry
5. i ՛:. 2 Running the ¿-test
5.: : Two-sample ¿-tests in Excel
Solved exercises
Exercises
i
6 ANALYSIS OF VARIANCE
6.1 Introduction
6.1. i A note on the use of F-tables
6.2 Illustrations
6.2.1 Hypothetical swimming frequency data
6.2.2 Diurnal variation in precipitation
6.3 Analysis of variance with two categories
6.4 Testing the assumptions
6.5 Consequences of failure to meet assumptions
- 6.6 Implications for hypothesis tests when assumptions
are not met
6.6.1 Normality
6.6.2 Homoscedasticity
6.6.3 Independence of observations
6.7 The nonparametric Kruskal-Wallis test
6.7.1 Illustration: diurnal variation in precipitation
. 6.7.2 More on the Kruskal-Wallis test
6.8 The nonparametric median test
6.8. i Illustration
6.9 Contrasts
6.9. j A priori contrasts
6 6; One-way ANOVA in SPSS 21 for Windows
6.10.1 Data entry
6.10.2 Data analysis and interpretation
6.11 One-way ANOVA in Excel
Solved exercises
Exercises
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7 CORRELATION
7 1 Introduction and examples of correlation
7.2 More illustrations
7.2.1 Mobility and cohort size
7.2.2 Statewide infant mortality rates and income
7.3 A significance test for r
7.3.1 Illustration
7 4 The correlation coefficient and sample size
7.5 Spearmans rank correlation coefficient
7.6 Additional topics
7.6.1 The effect of spatial dependence on significance tests for
correlation coefficients
7.6.2 The modifiable area unit problem and spatial aggregation
7.7 Correlation in SPSS 21 for Windows
7.7.1 Illustration
7.8 Correlation in Excel
Solved exercises
Exercises
8 INTRODUCTION TO REGRESSION ANALYSIS
8.1 Introduction
8.2 Fitting a regression line to a set of bivariate data
8.2.1 Illustration: income levels and consumer expenditure
8.3 Regression in terms of explained and unexplained sums of squares
8.3.1 Illustration
8.4 Assumptions of regression
8.5 Standard error of the estimate
8.6 Tests for /3
8.6.1 Illustration
8.7 Illustration: state aid to secondary schools
8.8 Linear versus nonlinear models
8.9 Regression in SPSS 21 for Windows
8.9.1 Data input
8.9.2 Analysis
8.9.3 Options
8.9.4 Output
8.10 Regression in Excel
8. J , ] Data input
8.1R2 Analysis
Solved exercises
Exercises
Multiple regression
Multicoffinearity
Interpretation of coefficients in multiple regression
Adjusted r2
Misspecification error
Dummy variables
Dummy variable regression in a recreation planning example
Multiple regression illustration: species in the Galapagos Islands
՝ Model l:The kitchen-sink approach
4 4.d Missing values
Outliers and multicollinearity
■*4.4 Model 2 .
; ; Model 3
4.4,6 Model 4
•46 Variable selection
4.6 Categorical dependent variable
9.6.1 Binary response
9.7 A summary of some problems that can arise in regression analysis
9.8 Multiple and logistic regression in SPSS 2ifor Windows
8.8.1 Multiple regression
() .8,2 Logistic regression
Exercises
10 SPATIAL PATTERNS 289
1! 1 1 Introduction 289
i 8.2 The analysis of point patterns 290
9 2.1 Quadrat analysis 292
1 ՛ 2 2 Nearest neighbor analysis 295
9-.8 Geographic patterns in areal data 300
■ .3,1 An example using a chi-square test 300
1: ՝,8.2 Moran’s I 302
M 44 Local statistics 307
V■՛. 4.1 Introduction 307
! 6.4.2 Local Moran statistic 308
10.4.3 Getis’ G. statistic 309
U45 Finding Morans I using SPSS 2i for Windows 310
N.6 Finding Morans I using GeoDa 311
Exercises 313
xi
11 SOME SPATIAL ASPECT? OP REGRESSION ANALYSIS
11.1 Introduction
11 0 Spatial lag model, neighborhood-based explanatory variables, and
added-variable plots
11.3 Spatial regression: autocorrelated errors
11.4 Spatially varying parameters
i 1.4. i The expansion method
11.4.2 Geographically weighted regression
11.5 Illustration
11.5.1 Ordinary least squares
11.5.2 Added-variable plots
11.5.3 Spatial regression: autocorrelated errors
11.5.4 Expansion method
11.5.5 Geographically weighted regression
11.6 Spatial Regression with GeoDa 1.4.6
Exercises
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12 DATA REDUCTION: FACTOR ANALYSIS AND
CLUSTER ANALYSIS 333
12.1 Introduction 333
12.2 Factor analysis and principal components analysis 334
12.2.1 Illustration: 1990 Census data for Erie County, New York ՛ 335
12.2.2 Regression analysis on component scores 340
12.3 Cluster analysis 341
12.3.1 More on agglomerative methods 342
12.3.2 Illustration: 1990 Census data for Erie County, New York 343
12.4 Data reduction methods in SPSS 21 for Windows 349
12.4.1 Factor analysis 349
12.4.2 Cluster analysis 349
Exercises 350
EPILOGUE 354
ANSWERS FOR SELECTED EXERCISES 357
APPENDIX A: STATISTICAL TABLES 365
Table A. 1, Random digits 365
Table A.2 Normal distribution 368
Table A.3 Student’s ¿֊distribution 369
XU
Table — Cumulative distribution of students ¿-distribution 37
Table A3 F-distribution 37
Table x2 distribution 38(
APPENDIX. B: MATHEMATICAL CONVENTIONS AND NOTATION 3gt
b i Mathematical conventions 38·
Lib Mathematical notation 38·
il 2 I. More Examples 38?
APPENDIX C: REVIEW AND EXTENSION OF SOME
PROBABILITY THEORY 387՝
C. I Expected values 388
C.2 Variance of a random variable 3895
( 33 Covariance of random variables · 390*
Bibliography 391
Index 397
|
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| bvnumber | BV042186702 |
| callnumber-first | G - Geography, Anthropology, Recreation |
| callnumber-label | G70 |
| callnumber-raw | G70.3 |
| callnumber-search | G70.3 |
| callnumber-sort | G 270.3 |
| callnumber-subject | G - General Geography |
| classification_rvk | RB 10103 |
| ctrlnum | (OCoLC)901773744 (DE-599)BVBBV042186702 |
| dewey-full | 910.015195 |
| dewey-hundreds | 900 - History & geography |
| dewey-ones | 910 - Geography and travel |
| dewey-raw | 910.015195 |
| dewey-search | 910.015195 |
| dewey-sort | 3910.015195 |
| dewey-tens | 910 - Geography and travel |
| discipline | Geographie |
| edition | 4. ed. |
| format | Book |
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| id | DE-604.BV042186702 |
| illustrated | Illustrated |
| indexdate | 2024-12-20T17:04:22Z |
| institution | BVB |
| isbn | 9781446295724 9781446295731 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-027625826 |
| oclc_num | 901773744 |
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| owner_facet | DE-824 DE-29 DE-384 DE-19 DE-BY-UBM |
| physical | XVIII, 401 S. graph. Darst., Kt. |
| publishDate | 2015 |
| publishDateSearch | 2015 |
| publishDateSort | 2015 |
| publisher | SAGE |
| record_format | marc |
| spellingShingle | Rogerson, Peter A. Statistical methods for geography a student's guide Geografie Geography Statistical methods Geografie (DE-588)4020216-1 gnd Statistik (DE-588)4056995-0 gnd |
| subject_GND | (DE-588)4020216-1 (DE-588)4056995-0 |
| title | Statistical methods for geography a student's guide |
| title_auth | Statistical methods for geography a student's guide |
| title_exact_search | Statistical methods for geography a student's guide |
| title_full | Statistical methods for geography a student's guide Peter A. Rogerson |
| title_fullStr | Statistical methods for geography a student's guide Peter A. Rogerson |
| title_full_unstemmed | Statistical methods for geography a student's guide Peter A. Rogerson |
| title_short | Statistical methods for geography |
| title_sort | statistical methods for geography a student s guide |
| title_sub | a student's guide |
| topic | Geografie Geography Statistical methods Geografie (DE-588)4020216-1 gnd Statistik (DE-588)4056995-0 gnd |
| topic_facet | Geografie Geography Statistical methods Statistik |
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