Analysing Quantitative Data for Business and Management Students

1. Auflage 2015
ISBN: 978-1-4462-7353-1
Verlag: SAGE Publications Ltd

Buch, Englisch, 184 Seiten, Paperback, Format (B × H): 170 mm x 244 mm, Gewicht: 329 g

Reihe: Mastering Business Research Methods

In Analysing Quantitative Data, Charles A. Scherbaum and Kristen M. Shockley guide the reader through Understanding Quantitative Data Analysis, Basic Components of Quantitative Data Analysis, Conducting Quantitative Data Analysis, Examples of Quantitative Data Analysis and Conclusions. An appendix contains Excel Formulas.

Ideal for Business and Management students reading for a Master’s degree, each book in the series may also serve as reference books for doctoral students and faculty members interested in the method.

Part of SAGE’s Mastering Business Research Methods Series, conceived and edited by Bill Lee, Mark N. K. Saunders and Vadake K. Narayanan and designed to support researchers by providing in-depth and practical guidance on using a chosen method of data collection or analysis.

Autoren/Hrsg.

Scherbaum, Charles A.

Shockley, Kristen M.

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Management Forschung & Entwicklung (F&E), Innovation

Inhaltsverzeichnis

Introduction
Chapter 1: Understanding Quantitative Data Analysis
Chapter 2: Basic Components of Quantitative Data Analysis
Chapter 3: Conducting Quantitative Data Analysis
Chapter 4: Examples of Quantitative Data Analysis
Conclusions
Glossary
Appendix of Excel Formulas
References

Über Autor(innen)

Shockley, Kristen M.
Dr. Kristen M. Shockley is an Assistant Professor in the Psychology Department at Baruch College and the Graduate Center of the City University of New York. She received her Ph.D. in industrial/organizational psychology from the University of South Florida. Her main area of research focuses on understanding the intersection of employees’ work and family lives. Specifically, she has conducted research aimed at understanding organizational initiatives to help employees managing competing life demands (i.e., flexible work arrangements); research that explores the relationship between work-family conflict and health outcomes, including eating behaviors and physiological indicators of health; research that addresses the measurement and theoretical foundations of work-family interactions; and research targeted at understanding how dual-earner couples balance work and family roles.

Her research has been published in several journals, such as the Journal of Vocational Behavior, Journal of Management, Human Performance, Journal of Occupational Health Psychology, Journal of Mixed Methods Research, and Personnel Psychology and in numerous book chapters in edited books. Her scholarly work has been awarded through the Society for Industrial/Organizational Psychology’s 2010 Mary L. Tenopyr and the 2011 S. Rains Wallace awards. She enjoys teaching Introduction to Statistics at the undergraduate and master’s levels.

Scherbaum, Charles A.
Dr. Charles A. Scherbaum is an associate professor of psychology at Baruch College. His research focuses on personnel selection, cognitive ability testing, attitudes toward stigmatized employees, and applied psychometrics. He received his Ph.D. in industrial and organizational psychology from Ohio University.

Publications of his research have appeared in journals such as Personnel Psychology, Organizational Research Methods, Educational and Psychological Measurement, Journal of Business and Psychology, and Leadership Quarterly and in numerous book chapters in edited books. His research has been supported by the National Science Foundation and the Graduate Management Admission Council. Charles was one of the winners of the 2011 M. Scott Myers Award for Applied Research from the Society for Industrial and Organizational Psychology (APA Division 14). Charles is on the editorial boards of the Journal of Applied Psychology and the Journal of Business and Psychology. He is the past president of the Metropolitan New York Association for Applied Psychology.