Description
Efnisyfirlit
- 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 Vari
- 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
- 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
- Hypothesis Testing Step 5: Select Sample, Collect Data, Screen Data, Compute Statistic, and Determin
- 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 Co
- 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
- 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
- Hypothesis Testing Step 5: Select Sample, Collect Data, Screen Data, Compute Statistic, and Determin
- 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 Co
- 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
- 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
- Hypothesis Testing Step 5: Select Sample, Collect Data, Screen Data, Compute Statistic, and Determin
- 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 Co
- 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
- A Priori Power Analysis
- Hypothesis Testing Step 4: Choose Appropriate Statistic and Its Sampling Distribution to Test the H0
- Hypothesis Testing Step 5: Select Sample, Collect Data, Screen Data, Compute Statistic, and Determin
- 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 Co
- Magnitude of Treatment Effect—Post Hoc Effect Size
- Post Hoc Power
- Confidence Intervals of Mean Differences
- Formula ANCOVA Calculations of the Study Results
- Step 1: Calculations for the Dependent Variable LDA (Y)
- Step 2: Calculations for the Covariate Age (X)
- Step 3: Calculations of Covariance of Age X LDA
- Step 4: Adjustment of LDA (DV, Y) Based on the Covariate of Age (X)
- Step 5: Calculation of Adjusted Means
- ANCOVA Study Results
- Summary
- Problem Assignment
- Key Terms
- Chapter 11: Randomized Control Group and Repeated-Treatment Designs and Nonparametics
- Research Problem
- Study Variables
- Research Design
- Statistical Analyses
- 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)
- Hypothesis Testing Step 3: Decide on a Risk Level (Alpha) of Rejecting the True H0 Considering Type
- 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
- Hypothesis Testing Step 5: Select Sample, Collect Data, Screen Data, Compute Statistic, and Determin
- Study Data Diagnostics
- Summary of Underlying Assumptions Findings
- Kruskal-Wallis One-Way Analysis of Variance of the Omnibus H0
- K-W One-Way ANOVA Results
- Hypothesis Testing Step 6: Make Decision Regarding the H0 and Interpret Post Hoc Effect Sizes
- Post Hoc Multiple Comparisons of Means
- Mann-Whitney U Statistical Analysis
- Magnitude of Treatment Effect—Post Hoc Effect Size and Post Hoc Power
- Formula Calculations
- Study Results
- Nonparametric Research Problem Two: Friedman’s Rank Test for Correlated Samples and Wilcoxon’s Match
- A Priori Power Analysis for Friedman and Wilcoxon Statistical Analyses
- Friedman’s Repeated Measures Analysis of Variance of the Omnibus H0
- Wilcoxon’s Statistical Analysis
- Magnitude of Treatment Effect—Post Hoc Effect Size and Post Hoc Power for Nonparametric Research P
- Formula Calculations for Friedman’s Rank Test and Wilcoxon’s Matched-Pairs Signed-Ranks Test
- Nonparametric Research Problem Two Results
- Summary
- Problem Assignment
- Key Terms
- Chapter 12: Bivariate and Multivariate Correlation Methods Using Multiple Regression Analysis
- Research Problem
- Study Variables
- Research Method
- Statistical Analysis: Bivariate Correlation and Multiple Regression
- 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)
- Hypothesis Testing Step 3: Decide on a Risk Level (Alpha) of Rejecting the True H0 Considering Type
- A Priori Power Analysis
- Hypothesis Testing Step 4: Choose Appropriate Statistic and Its Sampling Distribution to Test the H0
- Hypothesis Testing Step 5: Select Sample, Collect Data, Screen Data, Compute Statistic, and Determin
- Sample Selection and Assignment
- Study Data Diagnostics
- Univariate Outlier Analysis
- Multivariate Outlier Analysis
- General Screening of Correlation Coefficients
- Assessment of Multicollinearity and Singularity
- Assessment of Normality, Linearity, and Homoscedasticity of Residuals
- Sequential Multiple Regression Analysis
- Hand Calculations of Statistics
- Pearson Product-Moment Correlation Coefficient
- SPIScient and DSI Pearson Product-Moment Correlation
- SPIPract and DSI Pearson Product-Moment Correlation
- Partial Regression Coefficients
- Squared Multiple Correlation for Model 2
- Significance of R2 Using Analysis of Variance for Model 2
- F-Test of Change in R2
- Study Results
- Summary
- Problem Assignment
- Key Terms
- Chapter 13: Understanding Quantitative Literature and Research
- Interpretation of a Quantitative Research Article
- Identify the Research Questions in the Study
- Summary
- Problem Assignment
- References
- Index
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