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Applied Statistics and Multivariate Data Analysis for Business and Economics A Modern Approach Using SPSS, Stata, and Excel

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

14.08.2020

Verlag

Springer

Seitenzahl

474

Maße (L/B/H)

23,5/15,5/2,7 cm

Auflage

1st ed. 2019

Sprache

Englisch

ISBN

978-3-030-17769-0

Beschreibung

Rezension

“The book will be a very good textbook in applied statistics and multivariate data analysis for students in economics and business, and also for practitioners in firms that use those methods in their work.” (Anatoliy Swishchuk, zbMATH 1429.62002, 2020)

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

14.08.2020

Verlag

Springer

Seitenzahl

474

Maße (L/B/H)

23,5/15,5/2,7 cm

Auflage

1st ed. 2019

Sprache

Englisch

ISBN

978-3-030-17769-0

Herstelleradresse

Springer-Verlag GmbH
Tiergartenstr. 17
69121 Heidelberg
DE

Email: ProductSafety@springernature.com

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  • Produktbild: Applied Statistics and Multivariate Data Analysis for Business and Economics
  • Produktbild: Applied Statistics and Multivariate Data Analysis for Business and Economics
  • Contents

    Preface  2

    List of Figures  11

    List of Tables  18

    1     Statistics and Empirical Research   19

    1.1     Do Statistics Lie?  19

    1.2     Different Types of Statistics  21

    1.3     The Generation of Knowledge Through Statistics  24

    1.4     The Phases of Empirical Research   26

    1.4.1     From Exploration to Theory  26

    1.4.2     From Theories to Models  27

    1.4.3     From Models to Business Intelligence  31

    References  33

    2     From Disarray to Dataset  34

    2.1     Data Collection   34

    2.2     Level of Measurement  35

    2.3     Scaling and Coding   39

    2.4     Missing Values  41

    2.5     Outliers and Obviously Incorrect Values  43

    2.6     Chapter Exercises  43

    2.7     Exercise Solutions  44

    References  45

    3     Univariate Data Analysis  46

    3.1     First Steps in Data Analysis  46

    3.2     Measures of Central Tendency  54

    3.2.1     Mode or Modal Value  54

    3.2.2     Mean   55

    3.2.3     Geometric Mean   60

    3.2.4     Harmonic Mean   61

    3.2.5     The Median   64

    3.2.6     Quartile and Percentile  67

    3.3     The Boxplot: A First Look at Distributions  68

    3.4     Dispersion Parameters  72

    3.4.1     Standard Deviation and Variance  73

    3.4.2     The Coefficient of Variation   75

    3.5     Skewness and Kurtosis  76

    3.6     Robustness of Parameters  79

    3.7     Measures of Concentration   80

    3.8     Using the Computer to Calculate Univariate Parameters  83

    3.8.1     Calculating Univariate Parameters with SPSS  83

    3.8.2     Calculating Univariate Parameters with Stata  84

    3.8.3     Calculating Univariate Parameters with Excel  85

    3.9     Chapter Exercises  86

    3.10     Exercise Solutions  89

    References  93

    4     Bivariate Association   94

    4.1     Bivariate Scale Combinations  94

    4.2     Association Between Two Nominal Variables  95

    4.2.1     Contingency Tables  95

    4.2.2     Chi-Square Calculations  97

    4.2.3     The Phi Coefficient  102

    4.2.4     The Contingency Coefficient  105

    4.2.5     Cramer's V   107

    4.2.6     Nominal Associations with SPSS  107

    4.2.7     Nominal Associations with Stata  112

    4.2.8     Nominal Associations with Excel  112

    4.3     Association Between Two Metric Variables  114

    4.3.1     The Scatterplot  114

    4.3.2     The Bravais-Pearson Correlation Coefficient  117

    4.4     Relationships Between Ordinal Variables  121

    4.4.1     Spearman’s Rank Correlation Coefficient (Spearman’s rho)  123

    4.4.2     Kendall’s Tau (t)  128

    4.5     Measuring the Association Between Two Variables with Different Scales  135

    4.5.1     Measuring the Association Between Nominal and Metric Variables  135

    4.5.2     Measuring the Association Between Nominal and Ordinal Variables  138

    4.5.3     Association between Ordinal and Metric variables  139

    4.6     Calculating Correlation with a Computer  141

    4.6.1     Calculating Correlation with SPSS  141

    4.6.2     Calculating Correlation with Stata  142

    4.6.3     Calculating Correlation with Excel  143

    4.7     Spurious Correlations  146

    4.7.1     Partial Correlation   148

    4.7.2     Partial Correlations with SPSS  149

    4.7.3     Partial Correlations with Stata  150

    4.7.4     Partial Correlation with Excel  151

    4.8     Chapter Exercises  152

    4.9     Exercise Solutions  158

    References  164

    5     Classical Measurement Theory   165

    5.1     Sources of Sampling Errors  166

    5.2     Sources of Nonsampling Errors  169

    References  172

    6     Calculating Probability   173

    6.1     Key Terms for Calculating Probability  173

    6.2     Probability Definitions  176

    6.3     Foundations of Probability Calculus  180

    6.3.1     Probability Tree  180

    6.3.2     Combinatorics  181

    6.3.3     The Inclusion–Exclusion Principle for Disjoint Events  187

    6.3.4     Inclusion–Exclusion Principle for Nondisjoint Events  188

    6.3.5     Conditional Probability  189

    6.3.6     Independent Events and Law of Multiplication   190

    6.3.7     Law of Total Probability  191

    6.3.8     Bayes’ Theorem   192

    6.3.9     Postscript: The Monty Hall Problem   193

    6.4     Chapter Exercises  197

    6.5     Exercise Solutions  200

    References  209

    7     Random Variables and Probability Distributions  210

    7.1     Discrete Distributions  212

    7.1.1     Binomial Distribution   212

    7.1.1.1     Calculating Binomial Distributions using Excel 215

    7.1.1.2     Calculating Binomial Distributions using Stata  216

    7.1.2     Hypergeometric Distribution   217

    7.1.2.1     Calculating Hypergeometric Distributions using Excel 220

    7.1.2.2     Calculating the Hypergeometric Distribution using Stata  221

    7.1.3     The Poisson Distribution   222

    7.1.3.1     Calculating the Poisson Distribution using Excel 224

    7.1.3.2     Calculating the Poisson Distribution using Stata  225

    7.2     Continuous Distributions  226

    7.2.1     The Continuous Uniform Distribution   228

    7.2.2     The Normal Distribution   231

    7.2.2.1     Calculating the Normal Distribution using Excel 241

    7.2.2.2     Calculating the Normal Distribution using Stata  242

    7.3     Important Distributions for Testing   243

    7.3.1     The Chi-Squared Distribution   243

    7.3.1.1     Calculating the Chi-Squared Distribution using Excel 245

    7.3.1.2     Calculating the Chi-Squared Distribution using Stata  246

    7.3.2     The t-Distribution   247

    7.3.2.1     Calculating the t-Distribution using Excel 249

    7.3.2.2     Calculating the t-Distribution using Stata  250

    7.3.3     The F-distribution   251

    7.3.3.1     Calculating the F-Distribution using Excel 252

    7.3.3.2     Calculating the F-Distribution using Stata  253

    7.4     Chapter Exercises  254

    7.5     Exercise Solutions  258

    References  268

    8     Parameter Estimation   269

    8.1     Point estimation   269

    8.2     Interval estimation   277

    8.2.1     The confidence interval for the mean of a population (m)  277

    8.2.2     Planning the sample size for mean estimation   284

    8.2.3     Confidence intervals for proportions  287

    8.2.4     Planning sample sizes for proportions  290

    8.2.5     The confidence interval for variances  291

    8.2.6     Calculating confidence intervals with the computer  292

    8.2.6.1     Calculating confidence intervals with Excel 292

    8.2.6.2     Calculating confidence intervals with SPSS  296

    8.2.6.3     Calculating confidence intervals with Stata  297

    8.3     Chapter Exercises  301

    8.4     Exercise Solutions  303

    References  306

    9     Hypothesis Testing   307

    9.1     Fundamentals of Hypothesis Testing   307

    9.2     One-Sample Tests  312

    9.2.1     One-sample Z-test (when s is known)  312

    9.2.2     One-sample t-test (when s is not known)  316

    9.2.3     Probability value (p-value)  319

    9.2.4     One-sample t-test with SPSS, Stata, and Excel  319

    9.3     Tests for two dependent samples  323

    9.3.1     The t-test for dependent samples  323

    9.3.1.1     The paired t-test with SPSS  328

    9.3.1.2     The paired t-test with Stata  329

    9.3.1.3     The paired t-test with Excel 331

    9.3.2     The Wilcoxon signed-rank test  332

    9.3.2.1     The Wilcoxon signed-rank test with SPSS  337

    9.3.2.2     The Wilcoxon signed-rank test with Stata  338

    9.3.2.3     The Wilcoxon signed-rank test with Excel 339

    9.4     Tests for two independent samples  340

    9.4.1     The t-test of two independent samples  340

    9.4.1.1     The t-test for two independent samples with SPSS  343

    9.4.1.2     The t-test for two independent samples with Stata  345

    9.4.1.3     The t-test for two independent samples with Excel 346

    9.4.2     The Mann-Whitney U test (Wilcoxon rank-sum test)  348

    9.4.2.1     The Mann-Whitney U test with SPSS  352

    9.4.2.2     The Mann-Whitney U test with Stata  353

    9.5     Tests for k independent samples  354

    9.5.1     Analysis of Variance (ANOVA)  354

    9.5.1.1     One-way Analysis of Variance (ANOVA)  355

    9.5.1.2     Two-way Analysis of Variance (ANOVA)  360

    9.5.1.3     Analysis of covariance (ANCOVA)  364

    9.5.1.4     ANOVA/ANCOVA with SPSS  367

    9.5.1.5     ANOVA/ANCOVA with Stata  368

    9.5.1.6     ANOVA with Excel 369

    9.5.2     Kruskal-Wallis test (H test)  371

    9.5.2.1     Kruskal-Wallis H Test with SPSS  376

    9.5.2.2     Kruskal-Wallis H Test with Stata  378

    9.6     Other Tests  379

    9.6.1     Chi-square test of independence  379

    9.6.1.1     Chi-square test of independence with SPSS  381

    9.6.1.2     Chi-Square Test of Independence with Stata  384

    9.6.1.3     Chi-Square Test of Independence with Excel 384

    9.6.2     Tests for normal distribution   386

    9.6.2.1     Testing for normal distribution with SPSS  388

    9.6.2.2     Testing for normal distribution with Stata  389

    9.7     Chapter Exercises  389

    9.8     Exercise Solutions  400

    References  415

    10     Regression Analysis  418

    10.1     First Steps in Regression Analysis  418

    10.2     Coefficients of Bivariate Regression   420

    10.3     Multivariate Regression Coefficients  425

    10.4     The Goodness of Fit of Regression Lines  426

    10.5     Regression Calculations with the Computer  429

    10.5.1     Regression Calculations with Excel  429

    10.5.2     Regression Calculations with SPSS and Stata  430

    10.6     Goodness of Fit of Multivariate Regressions  432

    10.7     Regression with an Independent Dummy Variable  433

    10.8     Leverage Effects of Data Points  435

    10.9     Nonlinear Regressions  437

    10.10     Approaches to Regression Diagnostics  441

    10.11     Chapter Exercises  447

    10.12     Exercise Solutions  454

    References  457

    11     Time Series and Indices  458

    11.1     Price Indices  459

    11.2     Quantity Indices  466

    11.3     Value Indices (Sales Indices)  468

    11.4     Deflating Time Series by Price Indices  469

    11.5     Shifting Bases and Chaining Indices  470

    11.6     Chapter Exercises  472

    11.7     Exercise Solutions  473

    References  475

    12     Cluster Analysis  476

    12.1     Hierarchical Cluster Analysis  477

    12.2     K-Means Cluster Analysis  493

    12.3     Cluster Analysis with SPSS and Stata  495

    12.4     Chapter Exercises  499

    12.5     Exercise Solutions  502

    References  503

    13     Factor Analysis  505

    13.1     Factor Analysis: Foundations, Methods, Interpretations  505

    13.2     Factor Analysis with SPSS and Stata  514

    13.3     Chapter Exercises  517

    13.4     Exercise Solutions  518

    References  519

    List of Formulas  520

    Appendix   532

    Appendix 1: The Standard Normal Distribution   533

    Appendix 2: The Chi-Squared Distribution   534

    Appendix 3: The Student’s t-Distribution   536

    Appendix 4: Critical Values for the Wilcoxon Signed-Rank Test  537

    Index   538