# Statistical Methods for Practice and Research: A Guide to Data Analysis Using SPSS

Books

• Chapters
• Front Matter
• Back Matter

## Dedication

To our parents

Shri Ram Saran and Smt. Sumitra

## Preface

For business managers and practicing researchers, many times it becomes difficult to solve the real life problems involving statistical methods using software packages. The books on managerial statistics do give a comprehensive picture of statistics as a facilitating tool for managerial decision making but they invariably fail in helping the manager/researcher in solving and getting results for practical problems. With the help of simple examples, these books very successfully explain simple calculation procedures as well as the concepts behind them. However manual calculations, being cumbersome, tiresome and error-prone can be successful only to the extent of explaining the concepts and not for solving the real life research problems involving huge amount of data.

For this reason, most of the practical statistical analyses is done with the help of an appropriate software package. A manager/researcher, is only required to prepare the input data and should be able to get the final result easily with the help of software packages, so that focused attention can be given to various other aspects of problem solving and decision making.

A wide variety of software packages such as SPSS, Minitab, SAS, STATA, S-PLUS etc. are available for statistical analyses. Microsoft Excel can also be used very successfully to solve a wide variety of problems. Some books on managerial statistics even provide with spreadsheet templates where different results can be obtained by changing the input data. However, without the practical knowledge of working with a specialized software package, such templates are not helpful beyond academic interest.

This book is an effort towards facilitating business managers and researchers in solving statistical problems using computers. We have chosen SPSS, which is a very comprehensive and widely available package for statistical analyses. We have illustrated its use with the help of simple practical problems. The objective is to make the readers understand how they can use various statistical techniques for their own research problems. Throughout the book, the point and click method has been used in place of writing the syntax, even though syntax has been provided for interested users at the end of each analysis. The advantage of the point and click method is that it does not require any advance knowledge of the syntax and altogether eliminates the need to learn different types of command for different analyses.

The book is aimed primarily at academic researchers, MBA students, doctoral, masters and undergraduate students of mathematics, management science, and various other science and social science disciplines, practicing managers, marketing research professionals etc. It is also expected to serve as a companion volume to any standard textbook of Statistics and Marketing Research and for use in such courses in business schools and engineering colleges.

The book comprises of 11 chapters. Chapter 1 presents a brief overview of SPSS. Chapter 2 gives an overview of basic statistical concepts with the aim of helping in a quick revision of basic concepts, which one commonly encounters while carrying out data analyses. For an in-depth understanding of these concepts, readers are advised to refer to any standard textbook on statistics. Chapter 3 presents the use of SPSS in calculating descriptive statistics and presenting a visual display of the data. Chapters 4 and 5 present statistical techniques for comparing means of two or more than two groups. Chapter 6 describes a chi-square test for discrete data. Correlation analyses is presented in Chapter 7, followed by multiple regression in Chapter 8 and logistic regression in Chapter 9. Finally, we present data reduction techniques and methods for establishing scale reliability in Chapter 10 and advanced data handling and manipulation techniques in Chapter 11.

The illustrations are based on the SPSS 16.0 version. However, earlier versions of SPSS (10, 11, 12, 13, 14, 15) are functionally not much different from this version. The users of the earlier versions will find it equally useful for their purpose. With this book, we hope, you can analyze your data on your own and appreciate the real use of statistics.

## Acknowledgements

Many people have made this book possible. We would especially like to thank our students and participants of the research methods workshops we conducted all over India for refining our thinking and for motivating us to write a text on this subject. Our sincere thanks are due to Andrew Delios for his unusual tutelage on finer aspects of data analyses. The publishing team at SAGE, New Delhi has been very helpful. Leela, Shweta, and Anindita need special mention for their patience and support during the publication process. We would also like to thank Chapal, without whose persistence this book would have never come out. Finally, we thank our families—Sanjaya's family: Nirmal, Kamakhsi, and Vikrant and Ajai's family: Deeksha and Dishita—for their continued support and encouragement, without which this project would not have been attempted, much less finished.

,
• ## Bibliography

and (1991). Multiple Regression: Testing and Interpreting Interactions. Newbury Park, CA: Sage Publications.
(2002). Theory-Based Data Analysis for the Social Sciences. Thousand Oaks, CA: Sage Publications.
and (1986). “The Moderator-Mediator Variable Distinction in Social Psychological Research: Conceptual, Strategic, and Statistical Considerations”, Journal of Personality and Social Psychology, 51: 1173–82. http://dx.doi.org/10.1037/0022-3514.51.6.1173
(1994). An Easy Guide to Factor Analysis. London: Routledge.
, , and (1999). “Sample Size in Factor Analysis”, Psychological Methods, 4: 84–99. http://dx.doi.org/10.1037/1082-989X.4.1.84
(1997). Multiple Regression in Behavior Research,
3rd Edition
. Orlando FL: Harcourt Brace.
and (1991). Measurement, Design, and Analysis: An Integrated Approach. Hillsdale, NJ: Lawrence Erlbaum.
, and (2002). Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Boston, MA: Houghton Mifflin.
(2002). Applied Multivariate Statistics for the Social Sciences,
4th Edition
. New Jersey: Lawrence Erlbaum Associates.
and (2001). Using Multivariate Statistics,
2nd Edition
. Boston: Allyn and Bacon.