A guide to data analysis using SPSS
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.
1. Introduction to SPSS
2. Basic Statistical Concepts
3. Summarizing Data: Descriptive Statistics
4. Comparing Means: One or Two Samples t-Tests
5. Comparing Means: Analysis of Variance
6. Chi-Square Test of Independence for Discrete Data
7. Correlation Analysis
8. Multiple Regression
9. Logistic Regression
10. Data Reduction and Scale Reliability: Factor Analysis
11. Advanced Data Handling in SPSS
About the Authors
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