Table of contents for Introduction to statistics and data analysis for the behavioral sciences / Robert S. Lockhart.


Bibliographic record and links to related information available from the Library of Congress catalog


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1. The Purpose of Statistical Data Analysis
The Overall Goal of Statistical Data Analysis
Variables

2. Graphical and Numerical Descriptions of Data
Displaying Data as Distributions of Frequencies
Numerical Descriptions of Frequency Distributions
Linear Transformations of Scale and z-Scores

3. Modeling Data and the Estimation of Parameters
Imperfect Predictions, Models, and Residuals
Estimating the Parameters of a Model
Fitting Models with Categorical Predictor Variables

4. Probabilities Distributions
The Law of Large Numbers and the Meaning of Probability
Discrete Probability Distributions
The Central Limit Theorem and the Normal
Distribution
Obtaining Probabilities for Normally Distributed Variables
The Normal Distribution as a Model for Residuals

5. Sampling Distributions and Interval Estimation
The Sampling Distribution of the Mean
Calculating Confidence Intervals
Interpreting Confidence Intervals

6. Experiments with Two Independent Groups
Independent Groups Design
Analyzing Data from Independent Group Designs with Two Treatments
Deciding Between Models Using the t-distribution Directly
Decision Error Rates: The Neyman-Pearson Tradition
Overview and Evaluation

7. Larger Experiments with Independent Groups--Analysis of Variance
Models for Experiments With More Than Two Conditions
Evaluating the Null Model: Analysis of Variance
The Analysis of Variance of Factorial Designs

8. Increasing the Precision of an Experiment
Choosing an Appropriate Value of n in Two-Condition Experiments
Reducing Residuals by Using Matched Pairs
Matching and Within-Subjects Designs with More than Two Conditions

9. Experiments with Quantitative Predictor and Response Variables--Simple Linear Regression Examples
The Linear Model (Review)
Making Predictions
Correlation
Assumptions and Factors Influencing Correlation and Regression

10. Analyzing Data From Studies With Categorical Predictor and Response
Variables (Count Data)
Models for Proportions
Testing Goodness of Fit
Testing Independence in Two-Way Tables

11. Review
An Overview of Statistical Data Analysis
Extensions

Appendixes


Library of Congress subject headings for this publication:
Social sciences -- Statistical methods.