Quantitative and Statistical Research Methods: From Hypothesis to Results | Firsttion ed. Edition

Details about Quantitative and Statistical Research Methods: From Hypothesis to Results:

Quantitative and Statistical Research Methods: From Hypothesis to Results is a step-by-step 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. Designed to breed confidence and independence in students as they master intermediate statistical methods, the format for 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.  After completion of the book, students will know how to plan research and conduct statistical analyses using several different procedures.  This book will allow students to apply quantitative methods immediately to their own research with less oversight by faculty.  CONTENTS: Chapter 1: Book Introduction and Overview: Pedagogical grounding and framework of the book; Beginning key terms and concepts will be defined and described; Developing an understanding of independent, dependent, and extraneous variables and operational definitions; Describing scales of measurement associated with variables used in studies; Applying the criteria for writing research questions and hypotheses; The hypothesis testing process used throughout the text will be detailed from both a combined Fisher-Neyman and Tukey-Jones approaches Chapter 2: Logical Steps of Conducting Quantitative Research Hypothesis-Testing Process: Discussion of the advantages and disadvantages of hypothesis testing; Description of the steps of the hypothesis testing process; obtaining information to enhance the hypothesis testing process Chapter 3: Maximizing Hypothesis Decisions Power Analysis and Cases per Variables Ratios: Discussion of the role of power in avoiding making Type I and Type II errors in statistical designs; Description of the elements (estimated effect size, alpha, and sample size) comprising power; Calculations of power by hand and using computer programs; Discussion of the use of case-per-variable ratios Chapter 4: Research Designs and Statistical Designs: Description of the components and examples of experimental research designs; Description of the components and examples of quasi-experimental research designs; Description of the components and examples of relationship and prediction research methods; Discussion of mean differences statistical designs using the family of analysis of variance methods; Discussion of mean rank differences statistical designs using the non-parametric statistics; Description of correlation analysis statistical designs using bivariate correlation and multiple regression; Description of research design and statistical design decision trees Chapter 5: Using SPSS: Startup procedures for SPSS; Naming and defining variables; Entering data; Examples of basic analyses; Examples of modifying data procedures Chapter 6: Diagnosing Study Data for Inaccuracies and Assumptions: Assuring data accuracy; Dealing with missing data; Identifying and dealing with univariate outliers; Identifying and dealing with normality-underlying assumption; Identifying and dealing with homogeneity of variance-underlying assumption Chapter 7: Randomized Post-test Only Control Group Design using a One-Way Analysis of Variance (ANOVA): Description of the research problem; Identification of independent and dependent variables, their operational definitions, and scales of measurement; Identification of the research design and methods used for the research problem; Establishing the omnibus null and alternative hypotheses in both symbolic and narrative formats; A discussion of setting the alpha criterion in relation to Type I and Type II errors; A Priori power analysis and discussion; A discussion of the criteria used to select a one-way ANOVA as the appropriate statistic for this research problem; Data entry procedures using SPSS; Data screening; Computing and interpreting the one-way ANOVA on the computer and by hand; Computing and interpreting the multiple comparisons using the Post Hoc Tukey HSD statistic on the computer and by hand; Computing and interpreting the post-hoc effects sizes (magnitude of experimental effects) eta-squared (·2) and omega- squared (É2) and confidence intervals using the computer and by hand; Writing the results of the research problem; Historical connections to the development of research and statistical methods Chapter 8: Randomized Pretest-Posttest Control Group Design using a Repeated-Measures ANOVA: Description of the research problem; Identification of independent and dependent variables, their operational definitions, and scales of measurement; Identification of the research design and methods used for the research problem; Establishing the omnibus null and alternative hypotheses in both symbolic and narrative formats; A discussion of setting the alpha criterion in relation to Type I and Type II errors; Sample size and power; A discussion of the criteria used to select a repeated-measures ANOVA as the appropriate statistic for this research problem; Data entry procedures using SPSS; Data screening procedures; Computing and interpreting the repeated-measures ANOVA on the computer and by hand;   Computing and interpreting three post hoc analyses: (1) paired- means comparisons, (2) trend analysis, and (3) contrasts of sets of means; Computing and interpreting the post-hoc effects sizes (magnitude of experimental effects) and confidence intervals using the computer and by hand; Writing the results of the research problem; Historical connections to the development of research and statistical methods Chapter 9: Randomized Factorial Experimental Design using a Factorial ANOVA: Description of the research problem; Identification of independent and dependent variables, their operational definitions, and scales of measurement; Identification of the research design and methods used for the research problem; Establishing the omnibus null and alternative hypotheses in both symbolic and narrative formats; A discussion of setting the alpha criterion in relation to Type I and Type II errors; Sample size and power; A discussion of the criteria used to select a factorial ANOVA as the appropriate statistic for this research problem; Data entry procedures using SPSS; Data screening procedures; Computing and interpreting the factorial ANOVA on the computer and by hand; Compute and interpret post hoc analyses: (1) interaction plots and (2) simple effects; Computing and interpreting the post-hoc effects sizes (magnitude of experimental effects) and confidence intervals using the computer and by hand; Writing the results of the research problem; Historical connections to the development of research and statistical methods; Applying statistical procedures and research methods in psychology to analyze and interpret a research article Chapter 10: Randomized Post-test Only Control Group Design using an Analysis of Covariance (ANCOVA): Description of the research problem; Identification of independent and dependent variables, their operational definitions, and scales of measurement; Identification of the research design and methods used for the research problem; Establishing the omnibus null and alternative hypotheses in both symbolic and narrative formats; A discussion of setting the alpha criterion in relation to Type I and Type II errors; A Priori Power Analysis and discussion; A discussion of the criteria used to select a one-way ANOVA as the appropriate statistic for this research problem; Data entry procedures using SPSS; Data screening procedures; Computing and interpreting the ANCOVA on the computer and by hand; Computing and interpreting the multiple comparisons among means on the computer and by hand; Computing and interpreting the post-hoc effects sizes and confidence intervals using the computer and by hand; Writing the results of the research problem; Historical connections to the development of research and statistical methods Chapter 11: Quasi-Experimental Designs using the Kruskal-Wallis One-Way ANOVA, Mann-Whitney U, Friedmans Rank Test, and Wilcoxons Matched-Pairs Signed-Ranks test: Description of the research problem; Identification of independent and dependent variables, their operational definitions, and scales of measurement; Identification of the research design and methods used for the research problem; Establishing the omnibus null and alternative hypotheses in both symbolic and narrative formats; A discussion of setting the alpha criterion in relation to Type I and Type II errors; A Priori Power Analysis and discussion; A discussion of the criteria used to select the non-parametric statistics as the appropriate statistics for this research problem; Data entry procedures using SPSS; Data screening procedures; Computing and interpreting the non-parametric statistics on the computer and by hand; Computing and interpreting the multiple comparisons on the computer and by hand; Computing and interpreting the post-hoc effects sizes and confidence intervals using the computer and by hand; Writing the results of the research problem; Historical connections to the development of research and statistical methods Chapter 12: Bivariate and Multivariate Correlation Methods using Multiple Regression Analysis: Description of the research problem; Identification of predictor and criterion variables, their operational definitions, and scales of measurement; Identification of the research method used for the research problem; Establishing the omnibus null and alternative hypotheses in both symbolic and narrative formats; A discussion of setting the alpha criterion in relation to Type I and Type II errors; A Priori Power Analysis and discussion; A discussion of the criteria used to select bivariate and multiple regression analyses as the appropriate statistics for this research problem; Data entry procedures using SPSS; Data screening procedures; Computing and interpreting the bivariate and multiple regression analyses on the computer and by hand; Computing and interpreting the post-hoc effects sizes and confidence intervals using the computer and by hand; Writing the results of the research problem; Historical connections to the development of research and statistical methods; Applying statistical procedures and research methods in psychology to analyze and interpret a research article