Understanding Statistics for the Social Sciences with IBM SPSS Understanding Statistics for the Social Sciences with IBM SPSS Robert Ho SPSS was acquired by IBM in October 2009 CRC Press Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 2018 by Taylor & Francis Group, LLC CRC Press is an imprint of Taylor & Francis Group, an Informa business No claim to original U. Government works Printed on acid-free paper International Standard Book Number-13: 978-1-138-74228-4 (Hardback) 978-1-138-74220-8 (Paperback) This book contains information obtained from authentic and highly regarded sources. Reasonable efforts have been made to publish reliable data and information, but the author and publisher can- not assume responsibility for the validity of all materials or the consequences of their use. The authors and publishers have attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained.
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Visit the Taylor & Francis Web site at http://www.com and the CRC Press Web site at http://www.com Contents Preface. Introduction to the Scientific Methodology of Research.2 The Scientific Approach versus the Layperson’s Approach to Knowledge.3 Between-Groups Design.3 The Univariate Approach.1 The Multivariate Approach.5 Hypothesis Testing and Probability Theory.2 Statistics and Scientific Research.6 Definition of Statistics. Introduction to SPSS.1 Learning How to Use the SPSS Software Program.2 Introduction to SPSS.1 Setting Up a Data File.4 Creating SPSS Data File.6 Saving and Editing Data File.3 SPSS Analysis: Windows Method versus Syntax Method.4 SPSS Analysis: Windows Method.5 SPSS Analysis: Syntax Method.2 Results and Interpretation.22 Section I Descriptive Statistics 3. Basic Mathematical Concepts and Measurement.1 Basic Mathematical Concepts.3 Types of Variables.1 IV and DV.2 Continuous and Discrete Variables.3 Real Limits of Continuous Variables.1 Ungrouped Frequency Distributions.1 SPSS: Data Entry Format.2 SPSS Windows Method.3 SPSS Syntax Method.5 Results and Interpretation.2 Grouped Frequency Distributions.1 Grouping Scores into Class Intervals.2 Computing a Frequency Distribution of Grouped Scores.4 SPSS Windows Method.5 SPSS Syntax Method.3 Percentiles and Percentile Ranks.2 Computation of Percentiles (Finding the Score below which a Specified Percentage of Scores will Fall).3 SPSS Syntax Method.4 Data Entry Format.5 SPSS Syntax Method.8 Data Entry Format.9 SPSS Syntax Method.12 Computation of Percentile Ranks (Finding the Percentage of Scores that Fall below a Given Score).13 Data Entry Format.14 SPSS Syntax Method.17 Data Entry Format.18 SPSS Syntax Method.1 Graphing Frequency Distributions.2 Data Entry Format.3 SPSS Windows Method.4 SPSS Syntax Method.5 SPSS Bar Graph Output.2 SPSS Windows Method.3 SPSS Syntax Method.4 SPSS Histogram Output.2 SPSS Windows Method.3 SPSS Syntax Method.4 SPSS Frequency Polygon Output.5 Cumulative Percentage Curve.2 SPSS Windows Method.3 SPSS Syntax Method.4 SPSS Cumulative Percentage Output.
Measures of Central Tendency.1 Why Is Central Tendency Important?.2 Measures of Central Tendency.3 The Arithmetic Mean.1 How to Calculate the Arithmetic Mean.2 SPSS Window Method.3 SPSS Syntax Method.5 How to Calculate the Mean from a Grouped Frequency Distribution.7 Calculating the Mean from Grouped Frequency Distribution Using SPSS.8 Data Entry Format.9 SPSS Syntax Method.11 The Overall Mean.13 How to Calculate the Overall Mean Using SPSS.14 Data Entry Format.15 SPSS Syntax Method.17 Properties of the Mean.1 Calculating the Median for Ungrouped Scores.2 Calculating the Median for Grouped Scores.3 Properties of the Median.1 SPSS Windows Method.2 SPSS Syntax Method.3 SPSS Histogram Output.4 The Mode for Grouped Scores.6 Comparison of the Mean, Median, and Mode.7 Measures of Central Tendency: Symmetry and Skewness. Measures of Variability/Dispersion.1 What Is Variability?.1 Calculating the Standard Deviation Using the Deviation Scores Method.2 Calculating the Standard Deviation Using the Raw Scores Method.5 Using SPSS to Calculate the Range, the Standard Deviation, and the Variance.1 SPSS Windows Method.2 SPSS Syntax Method. The Normal Distribution and Standard Scores.1 The Normal Distribution.2 Areas Contained under the Standard Normal Distribution.3 Standard Scores (z Scores) and the Normal Curve.1 Calculating the Percentile Rank with z Scores.2 SPSS Windows Method.3 SPSS Syntax Method.4 SPSS Data File Containing the First 10 Computed z Scores.5 Calculating the Percentage of Scores that Fall between Two Known Scores.6 Calculating the Percentile Point with z Scores.7 SPSS Windows Method.8 SPSS Syntax Method.9 Table Showing the 90th Percentile for the Set of 50 Exam Scores.10 Calculating the Scores that Bound a Specified Area of the Distribution.11 SPSS Windows Method.12 SPSS Syntax Method.13 Table from either Window or Syntax Methods for Displaying Lower and Upper Bound Scores Binding the Middle 70% of the EX11.SAV data set.14 Using z Scores to Compare Performance between Different Distributions.1 The Concept of Correlation.2 Linear and Nonlinear Relationships.3 Characteristics of Correlation.1 Magnitude (Strength) of Relationships.2 Direction of Relationships.4 Correlation Coefficient and z Scores.4 Converting Raw Scores into z Scores (SPSS Windows Method).5 Converting Raw Scores into z Scores (SPSS Syntax Method).6 SPSS Data File Containing the 6 Pairs of Computed z Scores.5 Pearson r and the Linear Correlation Coefficient.1 Example of the Pearson r Calculation.2 SPSS Windows Method.3 SPSS Syntax Method.4 The Calculated Pearson r.6 Some Issues with Correlation.1 Can Correlation Show Causality?.1 What Is Linear Regression?.2 Linear Regression and Imperfect Relationships.1 Scatter Plot and the Line of Best Fit.2 SPSS Windows Method (Scatter Plot and Line of Best Fit).3 SPSS Syntax Method (Scatter Plot).4 Scatter Plot with Line of Best Fit.5 Least-Squares Regression (Line of Best Fit): Predicting Y from X.6 How to Construct the Least-Squares Regression Line: Predicting Y from X.7 SPSS Windows Method (Constructing the Least- Squares Regression Line Equation).8 SPSS Syntax Method (Constructing the Least- Squares Regression Line Equation).10 Results and Interpretation. 176 Section II Inferential Statistics 11.
Statistical Inference and Probability.1 Introduction to Inferential Statistics.1 The Classical Approach to Probability.2 The Empirical Approach to Probability.3 Expressing Probability Values.4 Computing Probability: The Addition Rule and the Multiplication Rule.5 The Addition Rule.6 The Multiplication Rule.7 Using the Multiplication and Addition Rules Together.8 Computing Probability for Continuous Variables.1 Simple Random Sampling.2 Stratified Proportionate Random Sampling.4 Nonrandom Sampling Techniques: Systematic Sampling; Quota Sampling.5 Sampling with or without Replacement.4 Confidence Interval and Confidence Level.1 How to Calculate the Confidence Interval.2 SPSS Windows Method.3 SPSS Syntax Method. Introduction to Hypothesis Testing.1 Introduction to Hypothesis Testing.2 Types of Hypotheses.1 Research/Alternative Hypothesis.3 Hypotheses: Nondirectional or Directional.1 Level of Significance.2 Two-Tailed and One-Tailed Test of Significance.3 Type I and Type II Errors. Hypothesis Testing: t test for Independent and Correlated Groups.1 Introduction to the t test.1 SPSS Windows Method: Independent t test.2 SPSS Syntax Method.4 Results and Interpretation.3 Dependent/Correlated t test.1 SPSS Windows Method: Dependent t test.2 SPSS Syntax Method.4 Results and Interpretation. Hypothesis Testing: One-Way Analysis of Variance.1 One-Way Analysis of Variance.2 Scheffé Post Hoc Test.3 SPSS Windows Method: One-Way ANOVA.4 SPSS Syntax Method.6 Results and Interpretation.7 Post Hoc Comparisons.
Hypothesis Testing: Chi-Square Test.2 Chi-Square (χ2) Test.1 Chi-Square Goodness-of-Fit Test.2 SPSS Windows Method.3 SPSS Syntax Method.5 Results and Interpretation.3 Chi-Square (χ2) Test of Independence between Two Variables.1 SPSS Windows Method.2 SPSS Syntax Method.4 Results and Interpretation. 269 Preface This introductory textbook introduces students to basic statistical concepts. It is suitable for undergraduate students in the social sciences where statis- tics is a core component in their undergraduate program. The book presents clear explanation of basic statistical concepts, the manual calculation of sta- tistical equations, and offers an introduction to the SPSS software program and in particular how to conduct basic statistical analysis using this program via the popular ‘point-and-click’ method and the ‘syntax’ method.
In writing this book, I have presented (1) a comprehensive coverage/ explanation of basic statistical concepts, (2) instructions on statistical analysis using the conventional manual procedural steps, and (3) introducing first- year social sciences students to the powerful SPSS software program. A focal point of this book is to show students how easy it is to analyse data using SPSS once they have learned the basics. I believe that learning how to use this very useful and sophisticated statistical software package at the introductory class level has a number of distinct advantages. First, the traditional and con- ventional cookbook method of instruction simply requires the first-year stu- dent to blindly follow a set of procedural steps; while such a technique may yield the correct results, the step-by-step calculations are simply not mean- ingful to a lot of students and contribute very little to their understanding of the rationale of how the correct results were obtained.
Since the main focus of the analysis is on the interpretation of the obtained results (and not on the technique used to derive the results) it does not matter how the results were obtained as long as the obtained results are correct. In other words, it would be much more efficient to bypass the conventional cookbook method and learn how to conduct analysis via statistical software packages such as SPSS. A second advantage of learning the SPSS software package at the introduc- tory class level is that most social sciences students will employ this program in their later years of study. This is because SPSS is one of the most popular of the many statistical packages currently available.
Learning how to use this program at the very start of their academic journey not only familiarizes students with the utility of this program but also provides them with the experience to employ the program to conduct complex analyses in their later years of study. I hope that this book will serve as a useful resource/guide to all students as they begin their journey into the practical world of statistics! Robert Ho NO T E : The data sets and SPSS macros employed in the examples in this book can be accessed and downloaded from the following Internet address: http://www.com xiii Author Robert Ho earned his DPhil from Waikato University, New Zealand, in 1978. He was an associate professor (retired) in the Graduate School of Psychology at the Assumption University of Thailand. His research interests included quantitative methods, health psychology, and social psychology.
Robert passed away in March 2017 following a long battle with cancer. As an academic he was a fantastic Lecturer and Mentor who always had the time to help out with an analysis from the simple to the multivariate. As a long time friend, his loyalty, hospitality, guitar playing, love of music, and appreciation of food will be missed. xv 1 Introduction to the Scientific Methodology of Research 1.1 Introduction Some of the common questions many students ask when they begin their research in psychology are, ‘Why do we need to do research? After all, what has the conduct of research got to do with the study of human behavior? Can’t we simply study human behavior without recourse to understanding the techniques of scientific investigation, without recourse to hypothesis testing’, and of course, the mother of all questions, ‘without recourse to sta- tistical analysis?’ Fair questions! The simple answer is that without objective, empirical, scientific-based verification of social phenomena, science as we know it will simply cease to exist.
And without scientific-based empirical research, progress in knowledge, technology, and innovations will stagnate and possibly come to a screeching halt.