{"product_id":"statistical-analysis-of-geographical-data-9780470977040","title":"Statistical Analysis of Geographical Data","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eStatistics Analysis of Geographical Data: An Introduction provides a comprehensive and accessible introduction to the theory and practice of statistical analysis in geography.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003ePreface xi\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Dealing with data 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 The role of statistics in geography 1\u003c\/p\u003e \u003cp\u003e1.1.1 Why do geographers need to use statistics? 1\u003c\/p\u003e \u003cp\u003e1.2 About this book 3\u003c\/p\u003e \u003cp\u003e1.3 Data and measurement error 3\u003c\/p\u003e \u003cp\u003e1.3.1 Types of geographical data: nominal, ordinal, interval, and ratio 3\u003c\/p\u003e \u003cp\u003e1.3.2 Spatial data types 5\u003c\/p\u003e \u003cp\u003e1.3.3 Measurement error, accuracy and precision 6\u003c\/p\u003e \u003cp\u003e1.3.4 Reporting data and uncertainties 7\u003c\/p\u003e \u003cp\u003e1.3.5 Significant figures 9\u003c\/p\u003e \u003cp\u003e1.3.6 Scientific notation (standard form) 10\u003c\/p\u003e \u003cp\u003e1.3.7 Calculations in scientific notation 11\u003c\/p\u003e \u003cp\u003eExercises 12\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Collecting and summarizing data 13\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Sampling methods 13\u003c\/p\u003e \u003cp\u003e2.1.1 Research design 13\u003c\/p\u003e \u003cp\u003e2.1.2 Random sampling 15\u003c\/p\u003e \u003cp\u003e2.1.3 Systematic sampling 16\u003c\/p\u003e \u003cp\u003e2.1.4 Stratified sampling 17\u003c\/p\u003e \u003cp\u003e2.2 Graphical summaries 17\u003c\/p\u003e \u003cp\u003e2.2.1 Frequency distributions and histograms 17\u003c\/p\u003e \u003cp\u003e2.2.2 Time series plots 21\u003c\/p\u003e \u003cp\u003e2.2.3 Scatter plots 22\u003c\/p\u003e \u003cp\u003e2.3 Summarizing data numerically 24\u003c\/p\u003e \u003cp\u003e2.3.1 Measures of central tendency: mean, median and mode 24\u003c\/p\u003e \u003cp\u003e2.3.2 Mean 24\u003c\/p\u003e \u003cp\u003e2.3.3 Median 25\u003c\/p\u003e \u003cp\u003e2.3.4 Mode 25\u003c\/p\u003e \u003cp\u003e2.3.5 Measures of dispersion 28\u003c\/p\u003e \u003cp\u003e2.3.6 Variance 29\u003c\/p\u003e \u003cp\u003e2.3.7 Standard deviation 30\u003c\/p\u003e \u003cp\u003e2.3.8 Coefficient of variation 30\u003c\/p\u003e \u003cp\u003e2.3.9 Skewness and kurtosis 33\u003c\/p\u003e \u003cp\u003eExercises 33\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Probability and sampling distributions 37\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Probability 37\u003c\/p\u003e \u003cp\u003e3.1.1 Probability, statistics and random variables 37\u003c\/p\u003e \u003cp\u003e3.1.2 The properties of the normal distribution 38\u003c\/p\u003e \u003cp\u003e3.2 Probability and the normal distribution: z‐scores 39\u003c\/p\u003e \u003cp\u003e3.3 Sampling distributions and the central limit theorem 43\u003c\/p\u003e \u003cp\u003eExercises 47\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Estimating parameters with confidence intervals 49\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Confidence intervals on the mean of a normal distribution: the basics 49\u003c\/p\u003e \u003cp\u003e4.2 Confidence intervals in practice: the t‐distribution 50\u003c\/p\u003e \u003cp\u003e4.3 Sample size 53\u003c\/p\u003e \u003cp\u003e4.4 Confidence intervals for a proportion 53\u003c\/p\u003e \u003cp\u003eExercises 54\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Comparing datasets 55\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Hypothesis testing with one sample: general principles 55\u003c\/p\u003e \u003cp\u003e5.1.1 Comparing means: one‐sample z‐test 56\u003c\/p\u003e \u003cp\u003e5.1.2 p‐values 60\u003c\/p\u003e \u003cp\u003e5.1.3 General procedure for hypothesis testing 61\u003c\/p\u003e \u003cp\u003e5.2 Comparing means from small samples: one‐sample t‐test 61\u003c\/p\u003e \u003cp\u003e5.3 Comparing proportions for one sample 63\u003c\/p\u003e \u003cp\u003e5.4 Comparing two samples 64\u003c\/p\u003e \u003cp\u003e5.4.1 Independent samples 64\u003c\/p\u003e \u003cp\u003e5.4.2 Comparing means: t‐test with unknown population variances assumed equal 64\u003c\/p\u003e \u003cp\u003e5.4.3 Comparing means: t‐test with unknown population variances assumed unequal 68\u003c\/p\u003e \u003cp\u003e5.4.4 t‐test for use with paired samples (paired t‐test) 71\u003c\/p\u003e \u003cp\u003e5.4.5 Comparing variances: F‐test 74\u003c\/p\u003e \u003cp\u003e5.5 Non‐parametric hypothesis testing 75\u003c\/p\u003e \u003cp\u003e5.5.1 Parametric and non‐parametric tests 75\u003c\/p\u003e \u003cp\u003e5.5.2 Mann–whitney U‐test 75\u003c\/p\u003e \u003cp\u003eExercises 79\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Comparing distributions: the Chi‐squared test 81\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Chi‐squared test with one sample 81\u003c\/p\u003e \u003cp\u003e6.2 Chi‐squared test for two samples 84\u003c\/p\u003e \u003cp\u003eExercises 87\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Analysis of variance 89\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 One‐way analysis of variance 90\u003c\/p\u003e \u003cp\u003e7.2 Assumptions and diagnostics 99\u003c\/p\u003e \u003cp\u003e7.3 Multiple comparison tests after analysis of variance 101\u003c\/p\u003e \u003cp\u003e7.4 Non‐parametric methods in the analysis of variance 105\u003c\/p\u003e \u003cp\u003e7.5 Summary and further applications 106\u003c\/p\u003e \u003cp\u003eExercises 107\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Correlation 109\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Correlation analysis 109\u003c\/p\u003e \u003cp\u003e8.2 Pearson’s product‐moment correlation coefficient 110\u003c\/p\u003e \u003cp\u003e8.3 Significance tests of correlation coefficient 112\u003c\/p\u003e \u003cp\u003e8.4 Spearman’s rank correlation coefficient 114\u003c\/p\u003e \u003cp\u003e8.5 Correlation and causality 116\u003c\/p\u003e \u003cp\u003eExercises 117\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Linear regression 121\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Least‐squares linear regression 121\u003c\/p\u003e \u003cp\u003e9.2 Scatter plots 122\u003c\/p\u003e \u003cp\u003e9.3 Choosing the line of best fit: the ‘least‐squares’ procedure 124\u003c\/p\u003e \u003cp\u003e9.4 Analysis of residuals 128\u003c\/p\u003e \u003cp\u003e9.5 Assumptions and caveats with regression 130\u003c\/p\u003e \u003cp\u003e9.6 Is the regression significant? 131\u003c\/p\u003e \u003cp\u003e9.7 Coefficient of determination 135\u003c\/p\u003e \u003cp\u003e9.8 Confidence intervals and hypothesis tests concerning regression parameters 137\u003c\/p\u003e \u003cp\u003e9.8.1 Standard error of the regression parameters 137\u003c\/p\u003e \u003cp\u003e9.8.2 Tests on the regression parameters 138\u003c\/p\u003e \u003cp\u003e9.8.3 Confidence intervals on the regression parameters 139\u003c\/p\u003e \u003cp\u003e9.8.4 Confidence interval about the regression line 140\u003c\/p\u003e \u003cp\u003e9.9 Reduced major axis regression 140\u003c\/p\u003e \u003cp\u003e9.10 Summary 142\u003c\/p\u003e \u003cp\u003eExercises 142\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Spatial statistics 145\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Spatial data 145\u003c\/p\u003e \u003cp\u003e10.1.1 Types of spatial data 145\u003c\/p\u003e \u003cp\u003e10.1.2 Spatial data structures 146\u003c\/p\u003e \u003cp\u003e10.1.3 Map projections 149\u003c\/p\u003e \u003cp\u003e10.2 Summarizing spatial data 157\u003c\/p\u003e \u003cp\u003e10.2.1 Mean centre 157\u003c\/p\u003e \u003cp\u003e10.2.2 Weighted mean centre 157\u003c\/p\u003e \u003cp\u003e10.2.3 Density estimation 158\u003c\/p\u003e \u003cp\u003e10.3 Identifying clusters 159\u003c\/p\u003e \u003cp\u003e10.3.1 Quadrat test 159\u003c\/p\u003e \u003cp\u003e10.3.2 Nearest neighbour statistics 162\u003c\/p\u003e \u003cp\u003e10.4 Interpolation and plotting contour maps 162\u003c\/p\u003e \u003cp\u003e10.5 Spatial relationships 163\u003c\/p\u003e \u003cp\u003e10.5.1 Spatial autocorrelation 163\u003c\/p\u003e \u003cp\u003e10.5.2 Join counts 164\u003c\/p\u003e \u003cp\u003eExercises 171\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Time series analysis 173\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Time series in geographical research 173\u003c\/p\u003e \u003cp\u003e11.2 Analysing time series 174\u003c\/p\u003e \u003cp\u003e11.2.1 Describing time series: definitions 174\u003c\/p\u003e \u003cp\u003e11.2.2 Plotting time series 175\u003c\/p\u003e \u003cp\u003e11.2.3 Decomposing time series: trends, seasonality and irregular fluctuations 179\u003c\/p\u003e \u003cp\u003e11.2.4 Analysing trends 180\u003c\/p\u003e \u003cp\u003e11.2.5 Removing trends (‘detrending’ data) 186\u003c\/p\u003e \u003cp\u003e11.2.6 Quantifying seasonal variation 187\u003c\/p\u003e \u003cp\u003e11.2.7 Autocorrelation 189\u003c\/p\u003e \u003cp\u003e11.3 Summary 190\u003c\/p\u003e \u003cp\u003eExercises 190\u003c\/p\u003e \u003cp\u003eAppendix A: Introduction to the R package 193\u003c\/p\u003e \u003cp\u003eAppendix B: Statistical tables 205\u003c\/p\u003e \u003cp\u003eReferences 241\u003c\/p\u003e \u003cp\u003eIndex 243\u003c\/p\u003e","brand":"John Wiley and Sons Ltd","offers":[{"title":"Default Title","offer_id":49402472923479,"sku":"9780470977040","price":32.25,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780470977040.jpg?v=1730480507","url":"https:\/\/bookcurl.com\/products\/statistical-analysis-of-geographical-data-9780470977040","provider":"Book Curl","version":"1.0","type":"link"}