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

Cleff, Thomas

Couverture souple

ISBN 10 : 3030177696 ISBN 13 : 9783030177690

Editeur : Springer, 2020

Synopsis

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

A propos du livre

À propos de l?auteur

Thomas Cleff is a Professor of Quantitative Methods for Business and Economics at Pforzheim University, Germany, and a Research Associate at the Centre for European Economic Research (ZEW), Mannheim, Germany. Since joining Pforzheim University in 2000, Cleff has spearheaded the development of an international dual-degree program, was appointed Vice Dean in 2012 and Dean of the Business School in 2014. He is an expert on international accreditation and partnership programmes between institutions of higher education. In 2013, he became a board member at the Network of International Business and Economic Schools (NIBES), and a member of the international advisory board at the South American Education Quality Accreditation Agency (EQUAA); in 2016 he joined the AACSB Initial Accreditation Committee. He has served as a Visiting Professor at several universities, including ESCEM Tours-Poitiers, France; Simon Fraser University, Vancouver, Canada; TEC de Monterrey, Mexico; and Gadjah Mada University, Indonesia.

Cleff holds degrees in Economics and Management from Pantheon-Sorbonne University, France and the University of Wuppertal, Germany. He was a Senior Researcher at the Centre for European Economic Research (ZEW) in Mannheim from 1997 to 2000, where he led a variety of international research projects in the fields of innovation and strategic management. His main research interests are in international marketing, white-collar crime, brand research, innovation, and industry studies.

Détails de l'édition

• Éditeur: Springer
• Date d'édition: 2020
• Langue: anglais
• ISBN 10: 3030177696
• ISBN 13: 9783030177690
• Reliure: Broché
• Nombre de pages: 500
• Coordonnées du fabricant: non disponible
• Personne responsable: CMN Printpool Inh. Mathis Neumann; https://www.also.com/ec/cms5/en_6000/6000/index.jsp; ; Friedrich-Karl-Str. 9; Hamburg; Allemagne