Record:   Prev Next
Author Martin, William E
Title Quantitative and Statistical Research Methods : From Hypothesis to Results
Imprint Somerset : John Wiley & Sons, Incorporated, 2012
©2012
book jacket
Edition 1st ed
Descript 1 online resource (498 pages)
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Series Research Methods for the Social Sciences Ser. ; v.42
Research Methods for the Social Sciences Ser
Note Intro -- Quantitative and Statistical Research Methods: From Hypothesis to Results -- Contents -- Tables and Figures -- Preface -- Acknowledgments -- The Authors -- Chapter 1: Introduction and Overview -- Review of Foundational Research Concepts -- Independent, Dependent, and Extraneous Variables -- Scales of Measurement of Variables -- Review of Foundational Statistical Information -- Measures of Central Tendency -- Measures of Variability (Dispersion) of Scores -- Variance of the Sample (s2) -- Standard Deviation of the Sample (s) -- Coefficient of Variation (C) -- Visual Representations of a Data Set -- The Normal Distribution -- Characteristics of the Normal Distribution -- Descriptive Statistical Applications of the Normal Distribution -- Inferential Statistical Applications of the Normal Distribution -- Summary -- Problem Assignment -- Key Terms -- Chapter 2: Logical Steps of Conducting Quantitative Research: Hypothesis-Testing Process -- Hypothesis-Testing Process -- Summary -- Problem Assignment -- Key Terms -- Chapter 3: Maximizing Hypothesis Decisions Using Power Analysis -- Balance Between Avoiding Type I and Type II Errors -- Illustration of Avoiding Making a Type I (Alpha) Error -- Illustration of Avoiding Making a Type II (Alpha) Error -- A Priori Power Analysis -- Summary -- Problem Assignment -- Key Terms -- Chapter 4: Research and Statistical Designs -- Formulating Experimental Conditions -- Reducing the Imprecision in Measurement -- Sampling Error -- Error of Measurement -- Controlling Extraneous Experimental Influences -- Methods of Controlling Extraneous Variables -- Internal Validity and Experimental Designs -- Internal Validity -- Experimental Designs -- Randomized Multiple Treatments and Control with Posttest-Only Design -- Randomized Multiple Treatments and Control with Pretest and Posttest Design
Quasi-Experimental Designs -- Repeated-Treatment Design with One Group -- Nonequivalent No-Treatment Control Group Time-Series Design -- Correlational Research Methods -- Choosing a Statistic to Use for an Analysis -- Summary -- Problem Assignment -- Key Terms -- Chapter 5: Introduction to IBM SPSS 20 -- The IBM SPSS 20 Data View Screen -- Naming and Defining Variables in Variable View -- Entering Variables -- Entering Data -- Examples of Basic Analyses -- Examples of Modifying Data Procedures -- Summary -- Problem Assignment -- Key Terms -- Chapter 6: Diagnosing Study Data for Inaccuracies and Assumptions -- Research Example -- Detecting Erroneous Data Entries -- Identifying and Dealing with Missing Data -- Identifying and Assessing Univariate Outliers -- Identifying and Assessing Univariate Outliers -- Screening and Making Decisions about Univariate Assumptions -- Skewness and Kurtosis -- Histograms -- Skewness Screening -- Kurtosis Screening -- Shapiro-Wilk Statistic -- Assessing Normal Q-Q Plots for Normality -- Summary of Our Screening Results for the Underlying Assumption of Normality -- Screening for Homogeneity of Variance -- Levene's Test -- One-Way Analysis of Variance Results -- Nontransformed One-Way ANOVA Results -- Transformed Screening and One-Way ANOVA Results -- Summary -- Problem Assignment -- Key Terms -- Chapter 7: Randomized Design Comparing Two Treatments and a Control Using a One-Way Analysis of Variance -- Research Problem -- Study Variables -- Independent Variable -- Dependent Variable -- Research Design -- Statistical Analysis: One-Way Analysis of Variance (ANOVA) -- Stating the Omnibus (Comprehensive) Research Question -- Omnibus Research Question (RQ) -- Hypothesis Testing Step 1: Establish the Alternative (Research) Hypothesis (Ha) -- Omnibus Narrative Alternative Hypothesis (Ha)
Hypothesis Testing Step 2: Establish the Null Hypothesis (H0) -- Hypothesis Testing Step 3: Decide on a Risk Level (Alpha) of Rejecting the True H0 Considering Type I and II Errors and Power -- Selecting Alpha (α) Considering Type I and Type II Errors -- A Priori Power Analysis -- Hypothesis Testing Step 4: Choose Appropriate Statistic and Its Sampling Distribution to Test the H0 Assuming H0 is True -- Hypothesis Testing Step 5: Select Sample, Collect Data, Screen Data, Compute Statistic, and Determine Probability Estimates -- Sample Selection and Assignment -- Study Data Diagnostics -- One-Way Analysis of Variance of the Omnibus H0 -- One-Way ANOVA Results -- Hypothesis Testing Step 6: Make Decision Regarding the H0 and Interpret Post Hoc Effect Sizes and Confidence Intervals -- Magnitude of Treatment Effect-Post Hoc Effect Size -- Post Hoc Power -- Post Hoc Multiple Comparisons of Means -- Confidence Intervals of Mean Differences -- Formula Calculations of the Study Results -- One-Way ANOVA Formula Calculations -- Post Hoc Effect Sizes -- Confidence Intervals (.95) for Mean Differences of Significant Pairs -- ANOVA Study Results -- Summary -- Problem Assignment -- Key Terms -- Chapter 8: Repeated-Treatment Design Using a Repeated-Measures Analysis of Variance -- Research Problem -- Study Variables -- Independent Variable -- Dependent Variable -- Research Design -- Statistical Analysis: Repeated-Measures Analysis of Variance -- Stating the Omnibus (Comprehensive) Research Question -- Omnibus Research Question (RQ) -- Hypothesis Testing Step 1: Establish the Alternative (Research) Hypothesis (Ha) -- Hypothesis Testing Step 2: Establish the Null Hypothesis (H0) -- Omnibus Narrative Null Hypothesis (H0) -- Hypothesis Testing Step 3: Decide on a Risk Level (Alpha) of Rejecting the True H0 Considering Type I and II Errors and Power
Selecting Alpha (α) Considering Type I and Type II Errors -- A Priori Power Analysis -- Hypothesis Testing Step 4: Choose Appropriate Statistic and Its Sampling Distribution to Test the H0 Assuming H0 Is True -- Hypothesis Testing Step 5: Select Sample, Collect Data, Screen Data, Compute Statistic, and Determine Probability Estimates -- Sample Selection and Assignment -- Study Data Diagnostics -- Repeated-Measures Analysis of Variance of the Omnibus H0 -- RM-ANOVA Results -- Post Hoc Multiple Comparisons of Pairs of Means -- Trend Analysis -- Hypothesis Testing Step 6: Make Decision Regarding the H0 and Interpret Post Hoc Effect Sizes and Confidence Intervals -- Magnitude of Treatment Effect-Post Hoc Effect Size -- Post Hoc Power -- Confidence Intervals of Mean Differences -- Formula Calculations of the Study Results -- Calculation of Sums of Squares -- Post Hoc Effect Size-Partial Eta-Squared -- Post Hoc Paired-Means Comparisons -- Study Results -- Summary -- Problem Assignment -- Key Terms -- Chapter 9: Randomized Factorial Experimental Design Using a Factorial ANOVA -- Research Problem -- Study Variables -- Independent Variables -- Dependent Variable -- Research Design -- Statistical Analysis: Factorial Analysis of Variance -- Stating the Omnibus (Comprehensive) Research Questions -- Omnibus Research Questions (RQs) -- Hypothesis Testing Step 1: Establish the Alternative (Research) Hypothesis (Ha) -- Jones and Tukey (2000) Recommended Process to Reach Conclusions -- Hypothesis Testing Step 2: Establish the Null Hypothesis (H0) -- Omnibus Narrative Null Hypotheses (H0) -- Hypothesis Testing Step 3: Decide on a Risk Level (Alpha) of Rejecting the True H0 Considering Type I and II Errors and Power -- Selecting Alpha (α) Considering Type I and Type II Errors -- A Priori Power Analysis
Hypothesis Testing Step 4: Choose Appropriate Statistic and Its Sampling Distribution to Test the H0 Assuming H0 Is True -- Hypothesis Testing Step 5: Select Sample, Collect Data, Screen Data, Compute Statistic, and Determine Probability Estimates -- Sample Selection and Assignment -- Study Data Diagnostics -- Assessing for Underlying Assumptions -- Two-Way Analysis of Variance of the Omnibus H0's -- Two-Way ANOVA Computer Analysis Results -- Hypothesis Testing Step 6: Make Decision Regarding the H0 and Interpret Post Hoc Effect Sizes and Confidence Intervals -- Magnitude of Treatment Effect-Post Hoc Effect Sizes -- Post Hoc Power -- Confidence Intervals of Mean Differences -- Formula Calculations of the Study Results -- Two-Way ANOVA Formula Calculations -- Post Hoc Effect Sizes -- Confidence Intervals (.99) for Mean Differences -- Study Results -- Summary -- Problem Assignment -- Key Terms -- Chapter 10: Analysis of Covariance -- Research Problem -- Study Variables -- Independent Variable -- Dependent Variable -- Covariate -- Research Design -- Statistical Analysis: Analysis of Covariance (ANCOVA) -- Stating the Omnibus (Comprehensive) Research Question -- Hypothesis Testing Step 1: Establish the Alternative (Research) Hypothesis (Ha) -- Hypothesis Testing Step 2: Establish the Null Hypothesis (H0) -- Hypothesis Testing Step 3: Decide on a Risk Level (Alpha) of Rejecting the True H0 Considering Type I and II Errors and Power -- A Priori Power Analysis -- Hypothesis Testing Step 4: Choose Appropriate Statistic and Its Sampling Distribution to Test the H0 Assuming H0 Is True -- Hypothesis Testing Step 5: Select Sample, Collect Data, Screen Data, Compute Statistic, and Determine Probability Estimates -- Sample Selection and Assignment -- Exploratory Data Analysis -- Analysis of Covariance of the Omnibus H0 -- ANCOVA Results -- Estimated Marginal Means
Hypothesis Testing Step 6: Make Decision Regarding the H0 and Interpret Post Hoc Effect Sizes and Confidence Intervals
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
Description based on publisher supplied metadata and other sources
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2020. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries
Link Print version: Martin, William E. Quantitative and Statistical Research Methods : From Hypothesis to Results Somerset : John Wiley & Sons, Incorporated,c2012 9780470631829
Subject SPSS (Computer file);Psychology -- Methodology.;Social sciences -- Methodology
Electronic books
Alt Author Bridgmon, Krista D
Record:   Prev Next