Data analysis and interpretation in the behavioral sciences /
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| Author / Creator: | Zechmeister, Eugene B., 1944- |
|---|---|
| Imprint: | Australia ; Belmont, CA : Thomson/Wadsworth, 2003. |
| Description: | xxiii, 522 p. : ill. ; 25 cm. |
| Language: | English |
| Subject: | |
| Format: | Print Book |
| URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/4811506 |
Table of Contents:
- Preface to the Instructor
- Preface to the Student
- Chapter 1. Introduction to the I-D-E-A Model of Data Analysis and Interpretation
- Introduction
- What Is/Are Data?
- Why (Specifically) and How (Generally) Do Scientists Do Research?
- What Is an Experiment?
- How Are Behavior and Events Measured?
- What Is the Role of Statistics in Behavioral Science Research?
- How Do I Get a Sample of Behavior?
- What Question Are You Asking?
- How Confident Can I Be of My Answer?
- An I-D-E-A for Data Analysis and Interpretation
- What You Have Learned and the Next Step
- Key Concepts
- Answers to Your Turn Questions
- Analyzing and Interpreting Data: Problems and Exercises
- Part 1. Inspecting and Describing Data from One Group
- Chapter 2. Inspecting Data Point by Point
- Introduction
- Cleaning Data
- How to Spot Suspicious Data Points
- A Hypothetical Data Set
- Using Tabular Inspection Methods
- What You Have Learned and the Next Step
- Key Concepts
- Answers to Your Turn Questions
- Analyzing and Interpreting Data: Problems and Exercises
- Chapter 3. Inspecting Distributions of Data
- Introduction
- Using Histograms to Inspect Distributions
- Frequency Polygons
- Graphing Nominal Data
- Transforming Data
- What to Do About Skewed Distributions
- Discarding Data
- What You Have Learned and the Next Step
- Key Concepts
- Answers to Your Turn Questions
- Analyzing and Interpreting Data: Problems and Exercises
- Chapter 4. Describing Data From One Group
- Introduction
- How Do We Describe Data?
- What Type of Data Are We Seeking to Describe?
- Measures of Central Tendency
- How Is Variability (Dispersion) Measured?
- The Standard Deviation and Standard Scores
- Data Description and the Normal Curve
- How Do We Use a Normal Distribution to Describe the Relative Positions of Scores?
- Comparing Apples and Oranges Again (or IQ and Height)
- What You Have Learned and the Next Step
- Key Concepts
- Answers to Your Turn Questions
- Analyzing and Interpreting Data: Problems and Exercises
- Part 2. I-D-E-A for a Study Involving a Single Mean
- Chapter 5. Estimating Confidence in a Mean
- Introduction
- Point Estimates and Interval Estimates
- What Is Sampling Variability?
- The Sampling Distribution of the Mean
- Probability and Normal Distributions
- Probability and the Sampling Distribution of the Mean
- How Do We Use a Sampling Distribution to Estimate Confidence in Our Finding?
- What You Have Learned and the Next Step
- Key Concepts
- Answers to Your Turn Questions
- Analyzing and Interpreting Data: Problems and Exercises
- Chapter 6. Constructing a Confidence Interval and Announcing Results
- Introduction
- The t Distribution
- Establishing a Confidence Interval for the Population Mean Based on the t Distribution
- Interpreting Confidence Intervals
- Increasing Precision and Confidence in Our Estimate
- A Slight Variation When There Is a Hypothesized Population Mean
- Announcing Results Based on a Single-Sample Mean
- What You Have Learned and the Next Step
- Key Concepts
- Answers to Your Turn Questions
- Analyzing and Interpreting Data: Problems and Exercises
- Part 3. I-D-E-A When There Are Two Means
- Chapter 7. Inspecting and Describing Data From Two Groups
- Introduction
- Getting Two Sets of Data to Compare
- Inspecting Two Distributions
- Describing Two Distributions
- Describing the Difference Between Two Samples
- Repeated Measures Designs
- What You Have Learned and the Next Step
- Key Concepts
- Answers to Your Turn Questions
- Analyzing and Interpreting Data: Problems and Exercises
- Chapter 8. Estimating Using Confidence Intervals
- Introduction
- Constructing Confidence Intervals for the Difference Between Two Means
- What Makes Confidence Intervals Wide or Narrow?
- Interpreting Differences Between Means
- What Does the Magnitude of the Effect Size Mean?
- Confidence Intervals for Difference Scores
- Effect Sizes for Difference Scores
- What You Have Learned and the Next Step
- Key Concepts
- Answers to Your Turn Questions
- Analyzing and Interpreting Data: Problems and Exercises
- Chapter 9. Estimating Using Null Hypothesis Significance Testing
- Introduction
- Testing Hypotheses
- Rejection Criteria
- The t Test for Independent Groups
- Assumptions Underlying t Tests
- What You Have Learned and the Next Step
- Key Concepts
- Answers to Your Turn Questions
- Analyzing and Interpreting Data: Problems and Exercises
- Chapter 10. Interpreting and Announcing Results
- Introduction
- Correctly Interpreting Null Hypothesis Significance Testing
- Type I and Type II Errors
- Pulling It All Together and Announcing Results
- Presenting Exact Probabilities
- What You Have Learned and the Next Step
- Key Concepts
- Answers to Your Turn Questions
- Analyzing and Interpreting Data: Problems and Exercises
- Part 4. I-D-E-A When There Are More Than Two Means
- Chapter 11. Inspecting, Describing, and Estimating Using Confidence Intervals
- Introduction
- Inspecting Data from an Independent Groups Design with One Independent Variable That Has Three or More Levels
- Describing the Data: Measures of Central Tendency and Variability
- Looking for Covariation
- Constructing Confidence Intervals for an Independent Groups Experiment
- Error Bars versus Confidence Intervals
- Obtaining a Measure of Effect Size for an Independent Groups Experiment with One Independent Variable
- Decisions About Differences Between Two Means in a Single-Factor Experiment
- What You Have Learned and the Next Step
- Key Concepts
- Answers to Your Turn Questions
- Analyzing and Interpreting Data: Problems and Exercises
- Chapter 12. Estimating Confidence Using Null Hypothesis Significance Testing and Announcing Results
- Introduction
- The Role of NHST in an Independent Groups Experiment with One Independent Variable (the E in I-D-E-A)
- The Logic of ANOVA
- An Illustration of ANOVA: Does Type of Presentation Affect Recall?
- Measures of Strength of Association for Independent Groups Designs
- Two-Group Comparisons in a Multi-Group Experiment
- Assessing Power in an Independent Groups Experiment
- Announcing Results (the A in I-D-E-A)
- What You Have Learned and the Next Step
- Key Concepts
- Answers to Your Turn Questions
- Analyzing and Interpreting Data: Problems and Exercises
- Chapter 13. I-D-E-A For Complex Designs
- Introduction
- Complex (Factorial) Designs
- Inspecting Data from a Complex (Factorial) Design
- Describing Results of a Complex Design: Cell Means, Main Effects, and Interaction
- Constructing Confidence Intervals for Means in a Complex Design
- Beyond 2 X 2
- ANOVA for a Complex Design
- Effect Size Measures for Complex Designs
- Announcing Results of a Complex Design
- What You Have Learned and the Next Step
- Key Concepts
- Answers to Your Turn Questions
- Analyzing and Interpreting Data: Problems and Exercises
- Part 5. I-D-E-A When Examining the Relationship Between Two Variables
- Chapter 14. Inspecting and Describing Correlational Data
- Introduction
- The Analysis Problem
- Constructing Scatterplots
- Describing Relationships Quantitatively
- The Original Correlation Formula
- Changing Scales
- What We Have Done So Far
- Inspecting the Relationships Between Two Variables
- Limitations of Correlational Analyses
- What Questions Do We Ask that Involve Two Variables?
- What You Have Learned and the Next Step
- Key Concepts
- Answers to Your Turn Questions
- Analyzing and Interpreting Data: Problems and Exercises
- Chapter 15. Estimating Confidence Using Confidence Intervals
- Introduction
- Confidence Intervals for Correlation Coefficients
- Interpreting Confidence Intervals of Correlation Coefficients
- Effect Sizes of Correlation Coefficients
- Interpreting the Effect Size of Correlations
- Avoiding Common Misunderstandings of Correlations
- What You Have Learned and the Next Step
- Key Concepts
- Answers to Your Turn Questions
- Analyzing and Interpreting Data: Problems and Exercises
- Chapter 16. Estimating Confidence Using Null Hypothesis Significance Testing and Announcing Results
- Introduction
- Null Hypotheses Involving Correlation Coefficients
- Testing Whether r is Different from .00
- Testing Whether r is Greater than .00
- Using a Table Instead of the t Formula
- Testing Whether r Differs from a Known [rho]
- Testing Whether Two Independent Correlations Differ from Each Other
- Pulling It All Together
- What You Have Learned and the Next Step
- Key Concepts
- Answers to Your Turn Questions
- Analyzing and Interpreting Data: Problems and Exercises
- Chapter 17. Making Predictions
- Introduction
- Graphing Linear Equations
- Graphing Variables Used in the Behavioral Sciences
- Calculating a Regression Equation
- Using Regression Predictions
- An Important Additional Detail About the Precision of Predictions
- Announcing the Results of a Regression Analysis
- Cautions in Using Regression Equations to Make Predictions
- What You Have Learned and the Next Step
- Key Concepts
- Answers to Your Turn Questions
- Analyzing and Interpreting Data: Problems and Exercises
- Part 6. I-D-E-A for Studies with Nominal Data
- Chapter 18. I-D-E-A with Nominal Data
- Introduction
- What Question Are You Asking?
- The I-D-E-A Model for a Proportion from a Single (Large) Sample
- NHST with Nominal Data
- Chi-square (x[superscript 2]) Goodness-of-Fit Test
- Chi-square (x[superscript 2]) Test of Independence
- Calculating an Effect Size for a Chi-Square Test of Independence
- Announcing Results of a Chi-Square Test of Independence
- What You Have Learned and the Next Step
- Key Concepts
- Answers to Your Turn Questions
- Analyzing and Interpreting Data: Problems and Exercises
- Appendix A
- A.1. Proportions of Area Under the Standard Normal Curve
- A.2. Critical Values of t
- A.3. Critical Values of F
- A.4. Transformation of r to Z[subscript r]
- A.5. Critical Values of r
- A.6. Critical Values of Chi-Square (x[superscript 2])
- Appendix B. A Brief Introduction to Power Analysis
- References
- Index
