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SPSS in Simple Steps is very useful for all students, researchers and faculty members who need to analyze quantitative data in their research work. The objective of the book is to help the students and researchers to undertake statistical analysis using PASW / SPSS software package. It is designed to be read in front of the computer screen. The book commences with an introduction to the PASW / SPSS software and provides a step-by-step approach for explaining procedures and executing PASW / SPSS commands. It provides a clear understanding of commands, procedures and functions required for carrying out statistical analysis. The book covers basic and essential features of PASW/SPSS. About The Author Dr. Kiran Pandya obtained M.Phil degree from University of Poona, for which he studied at Gokhale Institute of Politics & Economics. He was awarded the degree of Philosophy by the University of Sussex (U.K.). Commonwealth Commission in U.K. awarded the Academic Staff scholarship to pursue his doctoral studies. Currently, he is working as a Professor and Head in the Department of Research Methodology and Interdisciplinary Studies in Social Sciences, Veer Narmad South Gujarat University, Surat. He has more than twenty-eight years of teaching and research experience. Dr. Pandya has published number of papers in national and international journals and also has co-authored books on quantitative methods. He is actively involved in research and carrying out sponsored projects in the area of human development. Dr. Smruti Bulsari is currently a faculty in MBA programme of Veer Narmad South Gujarat University. She has obtained her doctoral degree and has more than ten years of teaching and research experience. She has also obtained master degrees in management and economics. She holds PG Diploma in Research Methodology and a Diploma in Computer Technology. Dr Bulsari has published papers in national and international journals. She has also co-authored books on SPSS and other subjects. She is associated with many research projects. She has delivered lectures in State-level and National-level workshops and training programmes in SPSS. Prof. Sanjay Sinha is currently attached to ITM Business School, Kharghar, Navi Mumbai as Associate Professor. Prof Sinha has around 12 years of corporate experience in different capacities in various organizations primarily in the BFSI segment. He quit the corporate world in 2006, when he was in the Vice President cadre and joined ITM group of Institutions as faculty in the area of Finance and Quantitative Techniques. He is currently heading the Department of Quantitative Techniques and teaches several courses in the areas of Finance as well. Prof Sinha is currently pursuing doctoral degree programme. Additionally he holds M Phil degree in Financial Management, Advanced Diploma in Financial Management, MBA in Financial Management, M. Sc in Statistics and B.Sc. in Physics, Mathematics and Statistics. Prof Sinha has also undergone a certificate programme in Capital Markets, Regulation and Compliance from University of Reading. He has publications in International Journals. The proficient team at Kogent Learning Solutions Inc. and Dreamtech Press has seized the market of computer books bringing excellent content in software development to the fore. The team is committed to excellence-excellence in the quality of content, excellence in the dedication of its authors and editors, excellence in the attention to detail, and excellence in understanding the needs of the readers. Table of Contents Overview of PASW Statistics Introduction to PASW 1.2 Menus 1.3 Tool Bar 1.4 Dialogue Box 1.5 Designate Window 1.6 Basic Steps for performing any Statistical Procedure Summary Data Management 2.1 Creating a Data File 2.2 Defining Variables 2.3 Entering the Data 2.4 Saving Data 2.5 Opening an existing Data File 2.6 Inserting Variables 2.7 Inserting Cases 2.8 Identifying Duplicate Cases 2.9 Identifying Unusual Cases 2.10 Sorting Cases 2.11 Merging a File 2.11.1 Add Cases 2.11.2 For Adding Variables 2.12 Data Aggregation 2.13 Splitting File 2.14 Selecting Cases 2.15 Listing Cases Summary Data Transformation 3.1 Computing a New Variable 3.2 Recoding Variables 3.3 Automatic Recode 3.4 Visual Binning 3.5. Rank Cases Summary Describing Data Numerically 4.1 Types of Measurement Scales 4.2 Summary Measures 4.2.1 Frequencies 4.2.2 Descriptive Statistics 4.2.3 Explore 4.2.4 Crosstabs Summary Describing Data Graphically 5.1 Line Chart 5.2 Pie Chart 5.3 Bar Chart 5.4 Histogram and the Standard Normal Curve 5.5 Box Plot 5.6 Scatter Diagram 5.7 P-P Plot 5.8 Q-Q Plot 5.9 Chart Builder 5.10 Formatting Charts Summary One Sample t-Test 6.1 Hypothesis Testing 6.1.1 Steps in Hypothesis Testing 6.1.2 Assumptions of Hypothesis Testing 6.2 Testing for Population Mean 6.3 Statistical and Practical Significance Summary Independent Sample t-Test 7.1 Assumptions of Independent Sample t-Test 7.2 Procedure for Testing for Differences in Means between Groups 7.3 Interpretation of Null Results 7.4 Effect Size Summary Paired Samples t-Test 8.1 Assumptions of Paired Samples t-Test 8.2 Procedure for Paired Sample t-test Summary One-Way ANOVA 9.1 Assumptions of One-Way ANOVA 9.2 Procedure for Testing for Differences in Means between Groups 9.3 Post Hoc Analysis 9.4 Procedure for undertaking Post Hoc Analysis 9.5 Measure of Association Summary One-Way Repeated Measures ANOVA 10.1 Assumptions of One-Way Repeated Measures ANOVA 10.2 Procedure for Undertaking One-Way Repeated Measures ANOVA Summary Two-Way ANOVA 11.1 Assumptions of two-way ANOVA 11.2 Procedure for Undertaking Two-Way ANOVA Summary Correlation 12.1 Assumptions of Correlations 12.2 Procedure for Undertaking Correlations 12.2.1 Bivariate Correlations 12.2.2 Rank Correlations 12.2.2 Partial Correlations Summary Multiple Regression 13.1 Assumptions of Linear Regression 13.2 Procedure for undertaking Linear Regression Summary Nonparametric Statistics 14.1 Runs Test 14.2 Chi-Square Test 14.3 Mann-Whitney U Test 14.4 Wilcoxon Signed Rank Test 14.5 Kruskal-Wallis Test Summary Logistic Regression Summary Reliability Analysis Summary Factor Analysis 17.1 Principal Components Method 17.2 Necessary Conditions for Undertaking Principal Component Analysis 17.3 Procedure for Undertaking Principal Component Analysis Summary Appendix-A Dataset for students.sav