Quantitative and Statistical Research Methods From Hypothesis to Results

by Martin, William E.; Bridgmon, Krista D.

• ISBN13: 9780470631829
• ISBN10: 0470631821
• Edition: 1st
• Format: Paperback
• Copyright: 2012-08-21
• Publisher: Jossey-Bass

Summary

Quantitative and Statistical Research Methodsoffers a guide for psychology, counseling, and education students in the use of statistics and research designs, combined with guidance on using SPSS in the course of their research. Each chapter covers a research problem, taking the student through identifying research questions and hypotheses; identifying, classifying, and operationally defining the study variables; choosing appropriate research designs; conducting power analysis; choosing an appropriate statistic for the problem; using a data set; conducting data screening and analyses (SPSS); interpreting the statistics; and writing the results related to the problem. Designed so students will know how to plan research and conduct statistical analyses using several different procedures.

Author Biography

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.

Table of Contents

Tables and Figures
Preface The Authors
Introduction and Overview
Review of Foundational Research Concepts Review of Foundational Statistical Information The Normal Distribution
Logical Steps of Conducting Quantitative Research: Hypothesis-Testing Process
Hypothesis-Testing Process
Maximizing Hypothesis Decisions Using Power Analysis
Balance between Avoiding Type I and Type II Errors
Research and Statistical Designs
Formulating Experimental Conditions Reducing the Imprecision in Measurement Controlling Extraneous Experimental Influences Internal Validity and Experimental Designs
Introduction to IBM SPSS	p. 20
The IBM SPSS Data View Screen Naming and Defining Variables in Variable View Entering Data Examples of Basic Analyses Examples of Modifying Data Procedures
Diagnosing Study Data for Inaccuracies and Assumptions
Research Example
Randomized Design Comparing Two Treatments and a Control Using a One-Way
Analysis of Variance Research Problem Study Variables Research Design Stating the Omnibus (Comprehensive) Research Question Hypothesis Testing
Establish the Alternative (Research) Hypothesis (Ha) Hypothesis Testing
Establish the Null Hypothesis (H0) Hypothesis Testing
Decide on a Risk Level (Alpha) of Rejecting the True H0 Considering Type I and II Errors and Power Hypothesis Testing
Choose Appropriate Statistic and Its Sampling Distribution to Test the H0 Assuming H0 Is True Hypothesis Testing
Select Sample, Collect Data, Screen Data, Compute Statistic, and Determine Probability Estimates Hypothesis Testing
Make Decision Regarding the H0 and Interpret Post Hoc Effect Sizes and Confidence Intervals Formula Calculations of the Study Results
Repeated-Treatment Design Using a Repeated-Measures Analysis of Variance Research Problem Study Variables Research Design Stating the Omnibus (Comprehensive) Research Question Hypothesis Testing
Establish the Alternative (Research) Hypothesis (Ha) Hypothesis Testing
Establish the Null Hypothesis (H0) Hypothesis Testing
Decide on a Risk Level (Alpha) of Rejecting the True H0 Considering Type I and II Errors and Power Hypothesis Testing
Choose Appropriate Statistic and Its Sampling Distribution to Test the H0 Assuming H0 Is True Hypothesis Testing
Select Sample, Collect Data, Screen Data, Compute Statistic, and Determine Probability Estimates Hypothesis Testing
Make Decision Regarding the H0 and Interpret Post Hoc Effect Sizes and Confidence Intervals Formula Calculations of the Study Results
Randomized Factorial Experimental Design Using a Factorial ANOVA Research Problem Study Variables Research Design Stating the Omnibus (Comprehensive) Research Question Hypothesis Testing
Establish the Alternative (Research) Hypothesis (Ha) Hypothesis Testing
Establish the Null Hypothesis (H0) Hypothesis Testing
Decide on a Risk Level (Alpha) of Rejecting the True H0 Considering Type I and II Errors and Power Hypothesis Testing
Choose Appropriate Statistic and Its Sampling Distribution to Test the H0 Assuming H0 Is True Hypothesis Testing
Select Sample, Collect Data, Screen Data, Compute Statistic, and Determine Probability Estimates Hypothesis Testing
Make Decision Regarding the H0 and Interpret Post Hoc Effect Sizes and Confidence Intervals Formula Calculations of the Study Results
Analysis of Covariance Research Problem Study Variables Research Design Stating the Omnibus (Comprehensive) Research Question Hypothesis Testing
Establish the Alternative (Research) Hypothesis (Ha) Hypothesis Testing
Establish the Null Hypothesis (H0) Hypothesis Testing
Decide on a Risk Level (Alpha) of Rejecting the True H0 Considering Type I and II Errors and Power Hypothesis Testing
Choose Appropriate Statistic and Its Sampling Distribution to Test the H0 Assuming H0 Is True Hypothesis Testing
Select Sample, Collect Data, Screen Data, Compute Statistic, and Determine Probability Estimates Hypothesis Testing
Make Decision Regarding the H0 and Interpret Post Hoc Effect Sizes and Confidence Intervals Formula ANCOVA Calculations of the Study Results ANCOVA Study Results
Randomized Control Group and Repeated-Treatment Designs and Nonparametics Research Problem Study Variables Research Design Stating the Omnibus (Comprehensive) Research Question Hypothesis Testing
Establish the Alternative (Research) Hypothesis (Ha) Hypothesis Testing
Establish the Null Hypothesis (H0) Hypothesis Testing
Decide on a Risk Level (Alpha) of Rejecting the True H0 Considering Type I and II Errors and Power Hypothesis Testing
Choose Appropriate Statistic and Its Sampling Distribution to Test the H0 Assuming H0 Is True Hypothesis Testing
Select Sample, Collect Data, Screen Data, Compute Statistic, and Determine Probability Estimates Hypothesis Testing
Make Decision Regarding the H0 and Interpret Post Hoc Effect Sizes Nonparametric Research Problem Two: Friedman's Rank Test for Correlated Samples and Wilcoxon's Matched-Pairs Signed-Ranks Test
Bivariate and Multivariate Correlation Methods Using Multiple Regression Analysis Research Problem Study Variables Research Method Stating the Omnibus (Comprehensive) Research Question Hypothesis Testing
Establish the Alternative (Research) Hypothesis (Ha) Hypothesis Testing
Establish the Null Hypothesis (H0) Hypothesis Testing
Decide on a Risk Level (Alpha) of Rejecting the True H0 Considering Type I and II Errors and Power Hypothesis Testing
Choose Appropriate Statistic and Its Sampling Distribution to Test the H0 Assuming H0 Is True Hypothesis Testing
Select Sample, Collect Data, Screen Data, Compute Statistic, and Determine Probability Estimates Hand Calculations of Statistics
Understanding Quantitative Literature and Research
Research Interpretation for Consumers Interpretation of a Quantitative Research Article
References Index
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