Understanding and Applying Research Design

"Duh" Science Versus "Huh" Science How Do We Know What We Know? Common Sense versus Science "Duh" Science "Huh Science" How Does Social Science Research Actually Work? What Are the Basic Assumptions of Science? Common Sense Is Not Enough: Errors in How We Observe Exercise: Should Marijuana Be Made Legal? Theories And Hypotheses What are Theories? What are Hypotheses? Operationalizing Variables Exercise: Operationalizing Concepts Independent and Dependent Variables Observation And Empirical Generalization Quantitative Designs Surveys Aggregate Data Exercise: Using the Religious Congregations and Membership Study Experiments Qualitative Designs Field Research Content Analysis Reliability and Validity Empirical Generalizations Correlational versus Causal Relationships Types of Research Pure Research Contents note continued: Applied Research Evaluation Research Action Research Ethics Human Subjects Abuses Protection of Humans in Research Professional Ethical Standards WHEEL OF SCIENCE: PROCEDURES OF RESEARCH Measurement Variables and Constants Operationalization Variation Constants Levels of Measurement Exercise: Levels of Measurement Units of Analysis Exercise: Units of Analysis Reliability and Validity of Measures Using Spss In Research Real-World Data Coverage of Statistical Procedures SPSS Basics General Features Using SPSS with General Social Survey Data Chi-Square And Contingency Table Analysis Contingency Tables Work Autonomy and Personal Health: An Example of a Contingency Table Using Chi Square to Determine the Significance of Research Findings Using SPSS for the Chi-Square Test of Independence The Crosstabs Procedure Effect Size: Contingency Coefficient Contents note continued: Effect Size: Phi Coefficient Effect Size: Cramer's V Creating and Analyzing the Contingency Table Data Directly Concluding Comments Learning From Populations: Censuses And Samples Censuses Samples Probability Sampling Types of Probability Samples Simple Random Sample Systematic Random Sampling Telephone Polls (Random-Digit Dialing) Stratified Random Samples Cluster Sampling Probability Proportional to Size Sampling and Statistics Potential Biases in Probability Samples Nonresponse Selective Availability Areal Bias Nonprobability "Samples" Convenience Samples Quota Sampling Snowball Sampling Exercise: Populations and Sampling Correlation The Nature of Correlation: Explore and Predict Different Measurement Values Correlation Measures Interpreting the Pearson's Correlation An Example of Correlation Assumptions for Correlation Contents note continued: Plotting the Correlation: The Scattergram Patterns of Correlations Strength of Correlations in Scattergrams Creating the Scattergram with SPSS Evaluating Pearson's r Correlation Using SPSS Interpreting r: Effect Size Correlation Influences Correlation is Not Causation An Example of Correlation Using SPSS Example Worksheet: Correlation Nonparametric Correlation Regression Understanding Regression through Correlation Regression Models Using SPSS to Understand Regression Specifying the Analyses in SPSS The SPSS Output Interpreting Multiple Regression: The Combined, Omnibus Findings Interpreting Multiple Regression: The Individual Predictor Findings Using MLR to Establish Causality Using MLR with Categorical Data Causation Criteria for Causation Time Correlation Multiple Causes of Income Nonspuriousness Antecedent Variables Contents note continued: Using Control Variables to Detect Spuriousness Intervening Variables The Effect of Income on Politics Income and Voting Example Regression Analysis and Testing for Spuriousness Detecting Spuriousness Regression Example Exercise: Testing Spuriousness in Crosstabs Exercise: Testing for Spuriousness in Regression WHEEL OF SCIENCE: DESIGNS OF RESEARCH Survey Research Nature of The Survey Three Types of Surveys Face-to-Face Interviews Telephone Interviews Questionnaires Online Survey Methods Online Surveys Online Forums Survey Item Construction Evaluating Closed-Ended Questions Biased Language Anchors Balanced Categories Double-Barreled Questions Variation in Survey Analyses Socially Acceptable Answers Respondent Knowledge Respondent Refusal Nonresponse in Questionnaire Data Bias in Surveys Studying Change with Surveys Contents note continued: Using Time in Survey Studies Cohort Studies Trend Studies Panel Studies Longitudinal Studies Censuses and Sampling Exercise: Survey Research in Action Aggregate Research Nature of Aggregate Data Areal and Social Units Rates Outliers Exercise: Putting It Together Exercise: Exploring Congregations in America Experiments Experimental Designs Pre-Experimental Designs The One-Shot Case Study One Group Pretest-Posttest Design The Static Group Selection Bias True Experimental Designs The Classic Experiment Solomon Four-Group Design Quasi-Experimental Designs Pre-Post Nonequivalent Control Group Design Fidelity of Experimental Design Experimental Settings Laboratory Experiments Field Experiments Natural/?Disaster Experiments Survey Experiments Ethics Contents note continued: Exercise: Experiments in Action Statistical Methods Of Difference: T Test Independent and Dependent Samples Independent t Test Example of Experiment Post Facto Designs Independent t Test: The Procedure Independent t Test Example The Variables Used in the Example The SPSS Results Effect Size for the Example Additional t Test Considerations 16.Analysis Of Variance The Nature of the ANOVA Design The Components of Variance The Process of ANOVA Calculating ANOVA Effect Size Post Hoc Analyses Assumptions of ANOVA Additional Considerations with ANOVA A Real-World Example of ANOVA Using SPSS for ANOVA Procedures Do the Different Independent Variable Groups Show Normally Distributed Dependent Variable Distributions? Are Variances Equal? Are Samples Independently Chosen? Are Interval Data on the Dependent Variable? SPSS Procedures with One-Way ANOVA Contents note continued: SPSS ANOVA Results for the Example Study The ANOVA Table The Post Hoc Analyses Field Research Selecting a Topic Relevance Accessibility Censorship Independent Funding Risk Entering the Field Neutralizing Observer Effects Taking Data in the Field Interviewing in the Field Field Notes Exercise: Field Research in Action Content Analysis Defining the Population Census or Sample? Coding in Content Analysis Coding Rolling Stone Exercise: Content Analysis of Popular Magazines STATISTICS AND DATA MANAGEMENT Statistical Procedures Unit A Writing The Statistical Research Summary Statistical Procedures Unit B THE NATURE OF INFERENTIAL STATISTICS Probability Probability, the Normal Curve, and p Values Populations (Parameters) and Samples (Statistics) The Hypothesis Test Contents note continued: Statistical Significance Practical Significance: Effect Size Data Management Unit A Use And Functions Of Spss Management Functions Reading and Importing Data Sort Additional Management Functions Split File Compute (Creating Indices) Analysis Functions Data Management Unit A: Uses and Functions Data Management Unit B Using Spss To Recode For T Test Using SPSS to Recode Questionnaire Items Recoding "health1" Recoding "fairearn" Data Management Unit B: Uses and Functions Data Management Unit C Descriptive Statistics Descriptive and Inferential Statistics Descriptive Statistics Descriptive Procedures for Nominal and Ordinal Data Using SPSS Graphs for Nominal and Ordinal Data Using SPSS Frequencies Command for Nominal- and Ordinal-Level Data Descriptive Procedures for Interval Data Numerical Procedures: Central Tendency Numerical Procedures: "Balance" and Variability Contents note continued: Obtaining Descriptive (Numerical) Statistics from SPSS Using SPSS Explore Obtaining Descriptive (Visual) Statistics from SPSS Data Management Unit C: Uses and Functions Statistical Procedures Unit C Z Scores The Nature of the Normal Curve The Standard Normal Score: z Score Calculating z Scores Using SPSS to Create z Scores Statistical Procedures Unit C Uses and Functions.