LEADER 00468nas 2200157z- 450 001 9910303485503321 035 $a(CKB)4330000001270935 035 $a(EXLCZ)994330000001270935 100 $a20180610cuuuuuuuu -u- - 101 0 $aeng 200 00$aPrometeo : rivista settimanale di lettere, scienze ed arti 517 $aPrometeo 906 $aJOURNAL 912 $a9910303485503321 996 $aPrometeo : rivista settimanale di lettere, scienze ed arti$92278105 997 $aUNINA LEADER 11972oam 2200553M 450 001 9910149555303321 005 20240501153429.0 010 $a1-4987-5894-0 010 $a1-315-38043-9 010 $a1-4987-5889-4 035 $a(CKB)4210000000000658 035 $a(MiAaPQ)EBC4732249 035 $a(OCoLC)1001338171 035 $a(OCoLC-P)1001338171 035 $a(FlBoTFG)9781315380438 035 $a(BIP)56919501 035 $a(BIP)60876807 035 $a(EXLCZ)994210000000000658 100 $a20161028d2016 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aSimple statistical tests for geography /$fDanny McCarroll 205 $a1st ed. 210 1$aBoca Raton :$cChapman & Hall/CRC,$d2016. 215 $a1 online resource (359 pages) $cillustrations, graphs 225 0 $aChapman & Hall Book 311 08$a1-138-43040-4 311 08$a1-4987-5881-9 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aCover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Contents -- Preface -- Acknowledgements -- Author -- 1. Introduction -- 1.1 Is This the Book for You? -- 1.2 How to Use This Book -- 1.3 Why Bother with Statistics? -- 1.4 A Note for Lecturers and Teachers -- References -- 2. How to Use Statistics -- 2.1 Hypotheses -- 2.2 The Null Hypothesis -- 2.3 Bad Hypotheses -- 2.4 Multiple Working Hypotheses -- 2.5 Unbiased Sampling -- 2.6 Probability: Is It Just Luck? -- 2.7 One or Two-Tail Testing -- 2.8 Effect Size -- References -- 3. Different Kinds of Data -- 3.1 Kinds of Data -- 3.1.1 Nominal -- 3.1.2 Ordinal -- 3.1.3 Individual Measurements -- 3.2 Independent or Linked Data? -- 3.3 Assumptions -- 3.3.1 Checking for a 'Normal' or Gaussian Distribution -- 3.4 Choosing the Right Test -- References -- 4. Tools of the Trade -- 4.1 Introduction -- 4.2 Arithmetic -- 4.3 Using a Calculator -- 4.4 Spreadsheets -- 4.4.1 Assigning Ranks in a Spreadsheet -- 4.5 SPSS -- 4.6 R Commander -- 4.7 Descriptive Statistics -- 4.7.1 Measures of the Middle: Mean, Median and Mode -- 4.7.2 Measures of Spread or Dispersion: Range, Variance and Standard Deviation -- 4.7.3 Confidence Limits around the Mean -- 4.7.4 Measures of the Shape of a Distribution: Skewness and Kurtosis -- References -- 5. Single Sample Tests -- 5.1 Introduction -- 5.2 Binomial Test -- 5.2.1 When It Is Useful -- 5.2.2 What It Is Based On -- 5.2.3 How to Do It -- 5.2.3.1 Online Calculators -- 5.2.3.2 In a Spreadsheet -- 5.2.3.3 Companion Site Calculator -- 5.2.3.4 In SPSS -- 5.2.3.5 In R Commander -- 5.2.3.6 By Hand -- 5.2.4 Examples -- 5.2.4.1 Example: Yes or No Questionnaire Answers -- 5.2.4.2 Example: Is There a Gender Bias in My Sample? -- 5.2.4.3 Example: Have the Limestones Been Removed by Weathering? -- 5.2.4.4 Example: Are There Too Few Black Managers in English Football?. 327 $a5.3 One-Sample Chi-Square (?2) Test -- 5.3.1 Introduction -- 5.3.2 When It Is Useful -- 5.3.3 What It Is Based On -- 5.3.4 How to Do It -- 5.3.4.1 Companion Site Calculator -- 5.3.4.2 In a Spreadsheet -- 5.3.4.3 In R Commander -- 5.3.4.4 In SPSS -- 5.3.5 Examples -- 5.3.5.1 Example: Beautiful Beaches -- 5.3.5.2 Example: Ethnic Groups -- 5.3.5.3 Example: Dolphin Sightings -- 5.4 Kolmogorov-Smirnov One-Sample Test -- 5.4.1 When It Is Useful -- 5.4.2 What It Is Based On -- 5.4.3 How to Do It -- 5.4.4 Examples -- 5.4.4.1 Example: Are Levels of Agreement Equal? -- 5.4.4.2 Example: Is My Sample Representative? -- 5.5 One Sample Runs Test for Randomness -- 5.5.1 When It Is Useful -- 5.5.2 What It Is Based On -- 5.5.3 How to Do It -- 5.5.3.1 Companion Site Calculators -- 5.5.3.2 In SPSS -- 5.5.3.3 In R Commander -- 5.5.4 Examples -- 5.5.4.1 Example: Nominal Data and Small Sample Sizes -- 5.5.4.2 Example: Large Sample of Individual Numbers -- References -- 6. Two-Sample Tests for Counts in Two Categories -- 6.1 Introduction -- 6.2 Sign Test -- 6.2.1 When It Is Useful -- 6.2.2 What It Is Based On -- 6.2.3 How to Do It -- 6.2.4 Effect Size -- 6.2.5 Examples -- 6.2.5.1 Example: Checking Exam Improvement -- 6.2.5.2 Example: Crystal Healing -- 6.2.5.3 Example: Footpath Erosion -- 6.3 McNemar's Test for Significance of Changes -- 6.3.1 When It Is Useful -- 6.3.2 What It Is Based On -- 6.3.3 How to Do It -- 6.3.4 Effect Size -- 6.3.5 Small Samples -- 6.3.6 Correction for Continuity -- 6.3.7 How to Do It -- 6.3.7.1 Companion Site Calculator -- 6.3.7.2 Online Calculators -- 6.3.7.3 In R Commander -- 6.3.7.4 In SPSS -- 6.3.8 Examples -- 6.3.8.1 Example: Opinions on Fracking -- 6.3.8.2 Example: Land Management -- 6.3.8.3 Example: Golf Green Hydrophobicity (Bad Test) -- 6.4 Tests for Independent Samples Arranged as 2 × 2 Contingency Tables. 327 $a6.5 Risk Ratio and Odds Ratio -- 6.5.1 Risk Ratio -- 6.5.2 Odds Ratio -- 6.6 Confidence Limits of the Odds Ratio and Risk Ratio -- 6.6.1 How to Do It -- 6.6.1.1 Companion Site Calculator -- 6.6.1.2 Using an Online Calculator -- 6.6.1.3 In R Commander -- 6.6.1.4 In SPSS -- 6.7 Sample Size Assumptions -- 6.7.1 Calculating Expected Values -- 6.8 Chi-Square Test for a 2 × 2 Contingency Table -- 6.8.1 When It Is Useful -- 6.8.2 What It Is Based On -- 6.8.3 Calculating Chi-Square -- 6.8.4 Continuity Correction (Yates's Correction) -- 6.8.5 Effect Size: Cramer's V -- 6.9 Conducting the Chi-Square Test -- 6.9.1 Companion Site Calculator -- 6.9.2 Online Calculators -- 6.9.3 In R Commander -- 6.9.4 In SPSS -- 6.9.5 Examples -- 6.9.5.1 Example: Organic Produce -- 6.9.5.2 Example: Erratic Content -- 6.9.5.3 Example: Large Sample Parametric Approach -- 6.9.5.4 Example: Common Error with a Solution -- 6.10 Fisher's Exact Test -- 6.10.1 When It Is Useful -- 6.10.2 What It Is Based On -- 6.10.3 How to Do It -- 6.10.3.1 Real Statistics Resource Pack for Excel -- 6.10.3.2 Online Calculators -- 6.10.3.3 In R Commander -- 6.10.3.4 In SPSS -- 6.10.4 Examples -- 6.10.4.1 Example: Small Sample of Snails -- 6.10.4.2 Example: Start-Up Companies -- References -- 7. Two-Sample Tests for Counts in Several Categories -- 7.1 Introduction -- 7.2 Two-Sample Chi-Square Test -- 7.2.1 When It Is Useful -- 7.2.2 What It Is Based On -- 7.2.3 Expected Frequencies -- 7.2.4 Sample Size Assumptions -- 7.2.5 Strength of the Relationship (Cramer's V) -- 7.2.5.1 Calculating Cramer's V -- 7.2.5.2 Where Are the Differences? -- 7.2.6 How to Conduct a Two-Sample Chi-Square Test -- 7.2.6.1 Companion Site Calculators -- 7.2.6.2 Online Calculators -- 7.2.6.3 R Commander -- 7.2.6.4 In SPSS -- 7.2.7 Examples -- 7.2.7.1 Example: Garden Visitors -- 7.2.7.2 Example: Snails (Small Sample). 327 $a7.2.7.3 Example: Misuse of Chi-Square -- 7.2.7.4 Example: Common Mistake and a Solution -- 7.3 Fisher's Exact Test for More Than Two Categories -- 7.3.1 When It Is Useful -- 7.3.2 How to Do It -- 7.3.2.1 In R Commander -- 7.3.2.2 In SPSS -- 7.3.3 Examples -- 7.3.3.1 Example: Snails (Small Sample) -- 7.3.3.2 Example: Small Questionnaire -- 7.3.3.3 Example: Failed Test and a Solution -- 7.4 Two-Sample Tests for Counts in Ordered Categories -- 7.5 Kolmogorov-Smirnov Two-Sample Test -- 7.5.1 When It Is Useful -- 7.5.2 How to Perform the Kolmogorov-Smirnov Two-Sample Test with Counts in Categories -- 7.5.2.1 Equal Sample Sizes -- 7.5.2.2 Unequal Sample Sizes -- 7.5.3 One-Tail Testing -- 7.5.4 Effect Size -- 7.5.5 How to Do It -- 7.5.5.1 Companion Site Calculators -- 7.5.5.2 Real Statistics Resource Pack -- 7.5.5.3 In SPSS -- 7.5.6 Examples -- 7.5.6.1 Example: Different Shaped Distributions -- 7.5.6.2 Example: Likert Scale, Small Samples -- 7.5.6.3 Example: Likert Scale, Large Samples -- 7.5.6.4 Example: Odd Case with a Bimodal Distribution -- 7.6 Scoring Categorical Data for Parametric Tests -- 7.6.1 How to Code Categorical Data -- References -- 8. Two-Sample Tests for Individual Measurements -- 8.1 Introduction -- 8.2 Wilcoxon's Matched-Pairs Signed-Ranks Test -- 8.2.1 When It Is Useful -- 8.2.2 What It Is Based On -- 8.2.3 Tied Ranks -- 8.2.4 Effect Size -- 8.2.5 How to Do It -- 8.2.5.1 In a Spreadsheet -- 8.2.5.2 Real Statistics Resource Pack -- 8.2.5.3 Companion Site Calculator -- 8.2.5.4 Online Calculators -- 8.2.5.5 In R Commander -- 8.2.5.6 In SPSS -- 8.2.6 Examples -- 8.2.6.1 Example: Attitudes to Recycling -- 8.2.6.2 Example: Grazing and Plant Diversity -- 8.3 Paired-Samples Student's t-Test -- 8.3.1 When It Is Useful -- 8.3.2 Effect Size -- 8.3.3 How to Do It -- 8.3.3.1 In a Spreadsheet -- 8.3.3.2 Companion Site Calculator. 327 $a8.3.3.3 In R Commander -- 8.3.3.4 In SPSS -- 8.3.3.5 Using a Calculator -- 8.3.3.6 Online Calculators -- 8.3.4 Examples -- 8.3.4.1 Example: Examination Marks -- 8.4 Two-Sample Tests for Independent Data with Individual Measurements -- 8.5 Mann-Whitney U-Test -- 8.5.1 When It Is Useful -- 8.5.2 What It Is Based On -- 8.5.3 Dealing with Tied Ranks -- 8.5.4 Effect Size -- 8.5.5 How to Do It -- 8.5.5.1 Online Calculators -- 8.5.5.2 Real Statistics Resource Pack -- 8.5.5.3 In a Spreadsheet -- 8.5.5.4 Companion Site Calculator -- 8.5.5.5 Using R Commander -- 8.5.5.6 In SPSS -- 8.5.6 Examples -- 8.5.6.1 Example: Exam Performance and Gender -- 8.5.6.2 Example: Biochar -- 8.5.6.3 Example: Schmidt Hammer and Glacial Moraines -- 8.6 Student's t-Test for Two Independent Samples -- 8.6.1 When It Is Useful -- 8.6.2 What It Is Based On -- 8.6.3 Effect Size -- 8.6.4 How to Do It -- 8.6.4.1 In a Spreadsheet -- 8.6.4.2 Online Calculators -- 8.6.4.3 Companion Site Calculator -- 8.6.4.4 In R Commander -- 8.6.4.5 In SPSS -- 8.6.5 Examples -- 8.6.5.1 Example: Male Underperformance -- 8.7 Two Independent Samples: Tests for Difference in Variability -- 8.8 The F-Test for Equality of Variance -- 8.8.1 When It Is Useful -- 8.8.2 What It Is Based On -- 8.8.3 How to Do It -- 8.8.3.1 In a Spreadsheet or Companion Site Calculator -- 8.8.3.2 In R Commander -- 8.8.3.3 In SPSS -- 8.8.3.4 Online Calculators -- 8.8.4 Examples -- 8.8.4.1 Example: Organic Strawberries -- 8.9 Non-Parametric Tests for Equality of Variance -- 8.10 Siegel-Tukey Test -- 8.10.1 When It Is Useful -- 8.10.2 What It Is Based On -- 8.10.3 How to Do It -- 8.10.3.1 Online Calculators and Spreadsheets -- 8.10.3.2 In R Commander -- 8.10.3.3 In SPSS -- 8.10.4 Examples -- 8.10.4.1 Example: Extremity of Opinion -- 8.10.5 'Measuring from the Middle' Approach -- 8.11 Kolmogorov-Smirnov Two-Sample Test for Continuous Data. 327 $a8.11.1 When It Is Useful. 330 $aThis book is aimed directly at students of geography, particularly those who lack confidence in manipulating numbers. The aim is not to teach the mathematics behind statistical tests, but to focus on the logic, so that students can choose the most appropriate tests, apply them in the most convenient way and make sense of the results. Introductory chapters explain how to use statistical methods and then the tests are arranged according to the type of data that they require. Diagrams are used to guide students toward the most appropriate tests. The focus is on nonparametric methods that make very few assumptions and are appropriate for the kinds of data that many students will collect. Parametric methods, including Student's t-tests, correlation and regression are also covered. Although aimed directly at geography students at senior undergraduate and graduate level, this book provides an accessible introduction to a wide range of statistical methods and will be of value to students and researchers in allied disciplines including Earth and environmental science, and the social sciences. 606 $aGeography$xStatistical methods 615 0$aGeography$xStatistical methods. 676 $a519.5 700 $aMcCarroll$b Danny$01213022 801 0$bOCoLC-P 801 1$bOCoLC-P 906 $aBOOK 912 $a9910149555303321 996 $aSimple statistical tests for geography$92801273 997 $aUNINA