Data Analysis in Management with SPSS Software

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J.P. Verma

Data Analysis

in Management

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J.P. Verma

Research and Advanced Studies Lakshmibai National University

of Physical Education Gwalior, MP, India

ISBN 978-81-322-0785-6 ISBN 978-81-322-0786-3 (eBook) DOI 10.1007/978-81-322-0786-3

Springer New Delhi Heidelberg New York Dordrecht London Library of Congress Control Number: 2012954479

The IBM SPSS Statistics has been used in solving various applications in different chapters of the book with the permission of the International Business Machines Corporation,# SPSS, Inc., an IBM Company. The various screen images of the software are Reprinted Courtesy of International Business Machines Corporation,#SPSS. “SPSS was acquired by IBM in October, 2009.”

IBM, the IBM logo, ibm.com, and SPSS are trademarks of International Business Machines Corp., registered in many jurisdictions worldwide. Other product and service names might be trademarks of IBM or other companies. A current list of IBM trademarks is available on the Web at “IBM Copyright and trademark information” at www.ibm.com/legal/copytrade.shtml.

#Springer India 2013

This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Exempted from this legal reservation are brief excerpts in connection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Duplication of this publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher’s location, in its current version, and permission for use must always be obtained from Springer. Permissions for use may be obtained through RightsLink at the Copyright Clearance Center. Violations are liable to prosecution under the respective Copyright Law.

The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.

While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein.

Printed on acid-free paper

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To my elder sister Sandhya Mohan for

having me introduced in statistics

Brother-in-law Rohit Mohan for his

helping gesture

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Preface

While serving as a faculty of statistics for the last 30 years, I have experienced that the non-statistics faculty and research scholars in different disciplines find it difficult to use statistical techniques in their research problems. Even if their theoretical concepts are sound its troublesome for them to use statistical software. This book provides readers with a greater understanding of a variety of statistical techniques along with the procedure to use the most popular statistical software package SPSS.

The book strengthens the intuitive understanding of the material, thereby increasing the ability to successfully analyze data in the future. It enhances readers capability in using data analysis techniques to a broader spectrum of research problems.

The book is intended for the undergraduate and postgraduate courses along with pre-doctoral and doctoral course work on data analysis, statistics, and/or quantita-tive methods taught in management and other allied disciplines like psychology, economics, education, nursing, medical, or other behavioral and social sciences. This book is equally useful to the advanced researchers in the area of humanities and behavioural and social sciences in solving their research problems.

The book has been written to provide solutions to the researchers in different disciplines for using one of the powerful statistical software SPSS. The book will serve the students as a self-learning text of using SPSS for applying statistical techniques in their research problems.

In most of the research studies, data are analyzed using multivariate statistics which poses an additional problem for the beginners. These techniques cannot be understood without in-depth knowledge of statistical concepts. Further, several fields in science, engineering, and humanities have developed their own nomencla-ture assigning different names to the same concepts. Thus, one has to gather sufficient knowledge and experience in order to analyze their data efficiently. This book covers most of the statistical techniques including some of the most powerful multivariate techniques along with their detailed analysis and interpreta-tion of the SPSS output that are required by the research scholars in different discipline to achieve their research objectives.

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The USP of this book is that even without having the indepth knowledge of statistics, one can learn various statistical techniques and their applications on their own.

Each chapter is self-contained and starts with the topics like Introductory concepts, application areas, statistical techniques used in the chapter and step-by-step solved example with SPSS. In each chapter in depth interpretation of SPSS output has been made to help the readers in understanding the application of statistical techniques in different situations. Since the SPSS output generated in different statistical applications are raw and cannot be directly used for reporting hence model way of writing the results has been shown wherever it is required.

This book focuses on providing readers with the knowledge and skills needed to carry out research in management, humanities, and social and behavioral sciences by using SPSS. Looking at the contents and prospects of learning computing skills using SPSS, this book is a must for every researcher from graduate-level studies onward. Towards the end of each chapter, short answer questions, multiple-choice questions, and assignments have been provided as a practice exercise for the readers. The common mistakes like using two-tailed test for testing one-tailed hypothe-sis, using the term “level of confidence” for defining level of significance or using the statement like “accepting the null hypothesis” instead of “not able to reject the null hypothesis” have been explained extensively in the text so that the readers may avoid such mistakes during organizing and conducting their research work.

The faculty who uses this book will find it very useful as it presents many illustrations with either real or simulated data to discuss analytical techniques in different chapters. Some of the examples cited in the text are from my own and my colleagues’ research studies.

This book consists of 14 chapters. Chapter1 deals with the data types, data cleaning, and procedure to start SPSS on the system. Notations used throughout the book in using SPSS commands have been explained in this chapter. Chapter2deals with descriptive study. Different situations have been discussed under which such studies can be undertaken. The procedure of computing various descriptive statis-tics has been discussed in this chapter. Besides computing procedure through SPSS, a new approach has been shown towards the end of the second chapter to develop the profile graph which can be used for comparing different domains of the populations.

Chapter3 explains the chi-square and its different applications by means of solved examples. The step-by-step procedure of computing chi-square using SPSS has been discussed. Chi-square is the test of significance for association between the attributes, but it provides comparison of the two groups as well, in case of the responses being measured on the nominal scale. This fact has been discussed for the benefit of the readers.

Chapter4 explains the procedure of computing correlation matrix and partial correlations using SPSS. The emphasis has been given on how to interpret the relationships.

In Chapter5, computing multiple correlations and regression analysis have been discussed. Both the approaches of regression analysis in SPSS i.e. Stepwise and Enter methods have been discussed for estimating any measurable phenomenon.

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In Chapter 6, application of t-test in testing the significance of difference between groups in all the three situations, that is, in one sample, two independent samples, and two dependent samples, has been discussed in detail. Procedures of using one-tailed and two-tailed tests have been thoroughly detailed.

Chapter 7 explains the procedure of applying one-way analysis of variance (ANOVA) with equal and unequal groups for testing the significance of variability among group means. The graphical approach has been discussed for post hoc comparisons of means besides using thep-value concept.

In Chapter8, two-way ANOVA for understanding the causes of variation has been discussed in detail by means of solved examples using SPSS. The model way of writing the results has been shown, which the students should note. Procedure for doing interaction analysis has been discussed in detail by using the SPSS output.

In Chapter 9, the application of ANCOVA to study the role of covariate in experimental research has been discussed by means of a research example. Students can find the procedure of analyzing their data much easier after going through this chapter.

In Chapter10, cluster analysis technique has been discussed in detail for market segmentation. The readers will come to know about the situations where cluster analysis can be used in their research studies. Discussions of all its basic concepts have been elaborated so that even a non-statistician can also appreciate and use it for their research data.

Chapter11deals with the factor analysis, one of the most widely used multivari-ate statistical techniques in management research. By going through this chapter, the readers can understand to study the characteristics of a group of data by means of few underlying structures instead of a large number of parameters. The proce-dure of developing the test battery using the factor analysis technique has also been discussed in detail.

In Chapter 12, we have discussed discriminant analysis and its application in various research situations. By learning this technique, one can develop classifica-tory model in classifying a customer into any of the two categories based on their relevant profile parameters. The technique is very useful in classifying a customer as good or bad for offering various services in the area of banking and insurance.

Chapter 13 explains the application of logistic regression for probabilistic classification of cases into one of the two groups. Basics of this technique have been discussed before explaining the procedure in solving logistic regression with SPSS. Interpretations of each and every output have been very carefully explained for easy understanding of the readers.

In Chapter 14, multidimensional scaling has been discussed to find the brand positioning of different products. This technique is especially useful if the popular-ity of products is to be compared on different parameters.

At each and every step, care has been taken so that the readers can learn to apply SPSS and understand minutest possible detail of analysis discussed in this book. The purpose of this book is to give a brief and clear description of how to apply variety of statistical analysis using any version of SPSS. We hope that this book will

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provide students and researchers with a self-learning material of using SPSS to analyze their data.

Students and other readers are welcome to e-mail me their query related to any portion of the book at [email protected], to which timely reply will be sent. Professor (Statistics) J.P. Verma

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Acknowledgements

I would like to extend my sincere thanks to my professional colleagues Prof. Y.P. Gupta, Prof. S. Sekhar, Dr. V.B. Singh, Prof. Jagdish Prasad and Dr. J.P. Bhukar for their valuable inputs in completing this text. I must thank to my research scholars who always motivated me to solve varieties of complex research problems which has contributed a lot in preparing this text. Finally I must appreciate the effort of my wife Hari Priya who not only provided me the peaceful environment in preparing this text but also helped me in correcting the manuscript language and format to a great extent. Finally I owe my loving gesture to my children Prachi and Priyam who have provided me the creative inputs in the preparation this manuscript.

Professor (Statistics) J.P. Verma

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Data Analysis in Management with SPSS Software

J.P. Verma

Data Analysis

in Management

To my elder sister Sandhya Mohan for

having me introduced in statistics

Brother-in-law Rohit Mohan for his

helping gesture

Preface

Acknowledgements

Contents