Behavioral Research and Analysis: An Introduction to Statistics within the Context of Experimental Design

What Is Science? Scientific Method Identify Problem Formulate Hypothesis Conduct Pilot Study Collect Data Participant (Subject) Sampling Experimental and Control Groups Independent and Dependent Variables Describing Collected Data Test Hypothesis Generalize Results Replicate Experiment Goals, Principles, and Assumptions of Science Goals of Science Description Explanation Principles of Science Empirical Verification Assumptions of Science Determinism Limited Causality Contiguity of Events Five Basic Approaches to Scientific Research Correlation Approach Establishing Validity Using Multiple Predictors Establishing Test Reliability Developing Homogeneous Subgroups Case History Approach Solving Personal Problems Predicting and Subgrouping Field Study Approach Experimental Approach Advantages of Experimental Approach Contents note continued: Disadvantages of Experimental Approach Purposes of Experimentation Experimentation Versus Demonstration Manipulation Versus Selection of Independent Values Quasi-Experimental Approach Time Series Design Nonequivalent Control Group Design Summary Keyword Definitions Exercises Exercise Answers References Keywords Samples and Populations Consideration of Numbers in Statistics Continuous Versus Discrete Data Four General Scales of Measurement Scaling Behavioral Dimensions Graphical Methods of Description Univariate Frequency Distribution Determine Range Determine Number and Size Set Up Frequency Distribution Tally Scores Post Tallies Add f Column Graphing Results Frequency Polygon Histogram Other Types of Graphs Cumulative Frequency Distribution Univariate Descriptive Statistics Measures of Central Tendency Mode Median Mean Averaging Means Contents note continued: When to Use Different Measures of Central Tendency Centiles and Quartiles Measures of Dispersion, Variability, or Spread Range Semi-Interquartile Range Average Deviation Variance Standard Deviation Interpretation of Standard Deviation Standard Score Measures of Distribution Skewness Measures of Distribution Kurtosis Bivariate Frequency Distributions Graphing Relationship Between Two Variables Shapes of Bivariate Frequency Distributions Correlation: The Pearson r Nature of Correlation Coefficients Pearson Product-Moment Correlation (r) Computation of Pearson r Effect of Range on Value or Coefficient Interpretation of Correlation Coefficients Interpretation of r2 (Coefficient of Determination) Other Correlation Coefficients Point Biserial rpb Computation of Point Biserial Contents note continued: Assumptions Underlying Point Biserial Biserial r Computation of Biserial rb Assumptions Underlying Biserial r Interpretation of Biserial r Spearman Rank Order Correlation Coefficient (Rho) Calculation of Spearman Rho Assumption Underlying Spearman Rho Use of Spearman Rho Kendall's Coefficient of Concordance (W) Computation of W Phi Coefficient (?) Computation of Phi Assumptions Underlying Phi Special Uses of Phi Coefficient Correlation Ratio (Eta) Calculation of Correlation Ratio Prediction and Concept of Regression Concept of Regression Computation of Regression Lines Equation for Straight Line Computation of Linear Regression Line Relation of byx and bxy to r Standard Error of Estimate Computation of SEest Interpretation of SEest Introduction to Inferential Statistics Contents note continued: Sampling Distribution of Means Example Central Limit Theorem Relationship of Sample Size to ?x Computing Standard Error of Mean ?x Sampling Distribution of Difference Between Two Means ?Dx Computing ?Dx Statistical Hypothesis Testing One-Tailed Versus Two-Tailed Hypotheses Type I and Type II Errors Power of Statistical Testing Two Randomized Groups Designs: t-Test for Independent Samples Two Randomized Groups (Between Groups) Design t-Test for Independent Data Concept of Degrees of Freedom Use of t-Test in Statistical Hypothesis Testing Limitations of Randomized Groups Design Two Matched Groups and Repeated Measures Designs: t-Test for Correlated Data Two Matched Groups Design t-Test for Correlated Data Computation of t for Correlated Data Repeated Measures (Within Subjects) Design Advantages and Uses of Repeated Measures Designs Contents note continued: Disadvantages of Repeated Measures Designs Counterbalancing in Repeated Measures Designs Using t-Test With Repeated Measures Design Nonparametric Analysis Mann-Whitney U-Test Assumptions of Mann-Whitney U-Test Computation of Mann-Whitney U-Test Explanation of U-Test Wilcoxon Matched-Pairs Signed-Ranks Test (T) Assumptions of Wilcoxon Test Computation of Wilcoxon Test Explanation of Wilcoxon Test Chi-Square Chi-Square Distribution Chi-Square Tests of Independence Computation of Degrees of Freedom for Chi-Square Tests Chi-Square Tests of Goodness of Fit Chi-Square Test for Goodness of Fit to Normal Computation of Chi-Square With Small Expected Frequencies Testing for Significance of Correlation Test for Significance of Phi (?) Testing for Significance of Pearson r and Spearman Rho Contents note continued: More Than Two Treatments Designs Reasons for Using More Than Two Treatments Using More Than Two Treatments May Yield a Different Answer To Obtain Fairly Precise Knowledge of the IV-DM Relationship To Study More Than Two Treatment Conditions Types of More Than Two Treatment Designs Single-Factor (Simple) Analysis of Variance Concept of Analysis of Variance (ANOVA) F-Test Rationale for F-Test Assumptions of F-Test Why Multiple t-Tests Should Not Be Used ANOVA for More Than Two Randomized Groups Design Computation of Sums of Squares Degrees of Freedom, Mean Squares, and F-Ratio Generalized ANOVA Summary Table Computational Example ANOVA for Repeated Measures Design Computation Example Post Hoc Analyses: Multiple Comparisons Among Means Tukey's WSD (Wholly Significant Difference) Contents note continued: Neuman-Keuls Test Bonferroni t-Test Scheffe Test for All Possible Comparisons Rationale for Factorial Designs Factorial Designs Two-Factor Designs Three-Factor Designs Four-Factor Designs Nested Designs Fully Crossed Designs Limitation of Nested Designs Types of Analysis of Variance Designs Between-Groups Designs Completely Within-Subjects (Repeated Measures) Designs Mixed Designs Between-Groups (Random Blocks) Two-Factor ANOVA Designs Rationale for Between-Groups ANOVA Designs Within-Subjects (Repeated Measures) Two-Factor ANOVA Designs Rationale for Within-Subjects ANOVA Designs Mixed Two-Factor ANOVA Designs Rationale for Mixed ANOVA Designs Contents note continued: References Planning and Conducting Study Surveying Literature Stating Problem and Hypothesis Defining Variables Selecting Design Developing Experimental Procedure Analyzing Results Techniques for Controlling Extraneous Variables Eliminating Conditions Holding Conditions Constant Balancing Conditions Counterbalancing Conditions Randomizing Conditions Conducting an Experiment Ethics Informed Consent Etiquette Writing Research Report General Comments General Format Abstract Introduction Purpose Crediting Sources Method Participants Apparatus Procedure Treatment of Data Results Discussion Book References Journal References Proceedings References Dissertation References Technical Report References Motion Picture References Newspaper and Magazine References Other References Tables and Figures Tables Contents note continued: Figures Additional Comments About Writing Scientific Reports References.