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Quantitative and Statistical Research Methods: From Hypothesis to Results

ISBN: 978-1-118-23457-0
496 pages
July 2012, Jossey-Bass
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Quantitative and Statistical Research Methods

This user-friendly textbook teaches students to understand and apply procedural steps in completing quantitative studies. It explains statistics while progressing through the steps of the hypothesis-testing process from hypothesis to results. The research problems used in the book reflect statistical applications related to interesting and important topics. In addition, the book provides a Research Analysis and Interpretation Guide to help students analyze research articles.

Designed as a hands-on resource, each chapter covers a single research problem and offers directions for implementing the research method from start to finish. Readers will learn how to:

  • Pinpoint research questions and hypotheses
  • Identify, classify, and operationally define the study variables
  • Choose appropriate research designs
  • Conduct power analysis
  • Select an appropriate statistic for the problem
  • Use a data set
  • Conduct data screening and analyses using SPSS
  • Interpret the statistics
  • Write the results related to the problem

Quantitative and Statistical Research Methods allows students to immediately, independently, and successfully apply quantitative methods to their own research projects.

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Tables and Figures ix

Preface xvii

The Authors xix

Chapter 1 Introduction and Overview 1

Review of Foundational Research Concepts 3

Review of Foundational Statistical Information 6

The Normal Distribution 14

Chapter 2 Logical Steps of Conducting Quantitative Research: Hypothesis-Testing Process 29

Hypothesis-Testing Process 30

Chapter 3 Maximizing Hypothesis Decisions Using Power Analysis 39

Balance between Avoiding Type I and Type II Errors 41

Chapter 4 Research and Statistical Designs 53

Formulating Experimental Conditions 54

Reducing the Imprecision in Measurement 55

Controlling Extraneous Experimental Influences 57

Internal Validity and Experimental Designs 59

Choosing a Statistic to Use for an Analysis 67

Chapter 5 Introduction to IBM SPSS 20 77

The IBM SPSS 20 Data View Screen 80

Naming and Defining Variables in Variable View 80

Entering Data 86

Examples of Basic Analyses 87

Examples of Modifying Data Procedures 96

Chapter 6 Diagnosing Study Data for Inaccuracies and Assumptions 99

Research Example 100

Chapter 7 Randomized Design Comparing Two Treatments and a Control Using a One-Way Analysis of Variance 129

Research Problem 130

Study Variables 131

Research Design 133

Stating the Omnibus (Comprehensive) Research Question 135

Hypothesis Testing Step 1: Establish the Alternative (Research) Hypothesis (Ha) 136

Hypothesis Testing Step 2: Establish the Null Hypothesis (H0) 137

Hypothesis Testing Step 3: Decide on a Risk Level (Alpha) of Rejecting the True H0 Considering Type I and II Errors and Power 138

Hypothesis Testing Step 4: Choose Appropriate Statistic and Its Sampling Distribution to Test the H0 Assuming H0 Is True 143

Hypothesis Testing Step 5: Select Sample, Collect Data, Screen Data, Compute Statistic, and Determine Probability Estimates 144

Hypothesis Testing Step 6: Make Decision Regarding the H0 and Interpret Post Hoc Effect Sizes and Confidence Intervals 162

Formula Calculations of the Study Results 166

Chapter 8 Repeated-Treatment Design Using a Repeated-Measures Analysis of Variance 183

Research Problem 184

Study Variables 185

Research Design 186

Stating the Omnibus (Comprehensive) Research Question 189

Hypothesis Testing Step 1: Establish the Alternative (Research) Hypothesis (Ha) 190

Hypothesis Testing Step 2: Establish the Null Hypothesis (H0) 191

Hypothesis Testing Step 3: Decide on a Risk Level (Alpha) of Rejecting the True H0 Considering Type I and II Errors and Power 192

Hypothesis Testing Step 4: Choose Appropriate Statistic and Its Sampling Distribution to Test the H0 Assuming H0 Is True 195

Hypothesis Testing Step 5: Select Sample, Collect Data, Screen Data, Compute Statistic, and Determine Probability Estimates 196

Hypothesis Testing Step 6: Make Decision Regarding the H0 and Interpret Post Hoc Effect Sizes and Confidence Intervals 216

Formula Calculations of the Study Results 218

Chapter 9 Randomized Factorial Experimental Design Using a Factorial ANOVA 231

Research Problem 232

Study Variables 232

Research Design 233

Stating the Omnibus (Comprehensive) Research Questions 237

Hypothesis Testing Step 1: Establish the Alternative (Research) Hypothesis (Ha) 238

Hypothesis Testing Step 2: Establish the Null Hypothesis (H0) 240

Hypothesis Testing Step 3: Decide on a Risk Level (Alpha) of Rejecting the True H0 Considering Type I and II Errors and Power 241

Hypothesis Testing Step 4: Choose Appropriate Statistic and Its Sampling Distribution to Test the H0 Assuming H0 Is True 247

Hypothesis Testing Step 5: Select Sample, Collect Data, Screen Data, Compute Statistic, and Determine Probability Estimates 248

Hypothesis Testing Step 6: Make Decision Regarding the H0 and Interpret Post Hoc Effect Sizes and Confidence Intervals 271

Formula Calculations of the Study Results 278

Chapter 10 Analysis of Covariance 297

Research Problem 298

Study Variables 299

Research Design 300

Stating the Omnibus (Comprehensive) Research Question 301

Hypothesis Testing Step 1: Establish the Alternative (Research) Hypothesis (Ha) 301

Hypothesis Testing Step 2: Establish the Null Hypothesis (H0) 302

Hypothesis Testing Step 3: Decide on a Risk Level (Alpha) of Rejecting the True H0 Considering Type I and II Errors and Power 302

Hypothesis Testing Step 4: Choose Appropriate Statistic and Its Sampling Distribution to Test the H0 Assuming H0 Is True 306

Hypothesis Testing Step 5: Select Sample, Collect Data, Screen Data, Compute Statistic, and Determine Probability Estimates 307

Hypothesis Testing Step 6: Make Decision Regarding the H0 and Interpret Post Hoc Effect Sizes and Confidence Intervals 324

Formula ANCOVA Calculations of the Study Results 327

ANCOVA Study Results 339

Chapter 11 Randomized Control Group and Repeated-Treatment Designs and Nonparametics 345

Research Problem 346

Study Variables 346

Research Design 347

Stating the Omnibus (Comprehensive) Research Question 349

Hypothesis Testing Step 1: Establish the Alternative (Research) Hypothesis (Ha) 349

Hypothesis Testing Step 2: Establish the Null Hypothesis (H0) 350

Hypothesis Testing Step 3: Decide on a Risk Level (Alpha) of Rejecting the True H0 Considering Type I and II Errors and Power 350

Hypothesis Testing Step 4: Choose Appropriate Statistic and Its Sampling Distribution to Test the H0 Assuming H0 Is True 354

Hypothesis Testing Step 5: Select Sample, Collect Data, Screen Data, Compute Statistic, and Determine Probability Estimates 355

Hypothesis Testing Step 6: Make Decision Regarding the H0 and Interpret Post Hoc Effect Sizes 370

Formula Calculations 376

Nonparametric Research Problem Two: Friedman’s Rank Test for Correlated Samples and Wilcoxon’s Matched-Pairs Signed-Ranks Test 382

Chapter 12 Bivariate and Multivariate Correlation Methods Using Multiple Regression Analysis 401

Research Problem 402

Study Variables 402

Research Method 403

Stating the Omnibus (Comprehensive) Research Question 405

Hypothesis Testing Step 1: Establish the Alternative (Research) Hypothesis (Ha) 405

Hypothesis Testing Step 2: Establish the Null Hypothesis (H0) 406

Hypothesis Testing Step 3: Decide on a Risk Level (Alpha) of Rejecting the True H0 Considering Type I and II Errors and Power 406

Hypothesis Testing Step 4: Choose Appropriate Statistic and Its Sampling Distribution to Test the H0 Assuming H0 Is True 407

Hypothesis Testing Step 5: Select Sample, Collect Data, Screen Data, Compute Statistic, and Determine Probability Estimates 407

Hand Calculations of Statistics 423

Chapter 13 Understanding Quantitative Literature and Research 439

Interpretation of a Quantitative Research Article 440

References 461

Index 465

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William E. Martin, EdD, is a professor and past chair of educational psychology in the College of Education, Northern Arizona University. He also served as senior scholar in the university's Faculty Research Center. His research areas are psychometric assessment, counselor development, psychosocial adjustment, and person-environment-based prevention and intervention methods.

Krista D. Bridgmon, PhD, is an assistant professor of psychology at Colorado State University-Pueblo. Her research areas are doctoral student attrition, stress and coping, school counseling, and sport psychology.

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