Introduction to Statistics and Data Analysis For the Behavioral Sciences

ISBN-10: 0716729741

ISBN-13: 9780716729747

Edition: 1998

List price: $112.99
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Description: Professor Lockhart here empasizes the link between scientific discovery and statistical techniques, focusing on the evaluation and comparison of models, and eventually integrating the various statistical methods into a single coherent whole.

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Book details

List price: $112.99
Copyright year: 1998
Publisher: Worth Publishers, Incorporated
Publication date: 12/15/1997
Binding: Hardcover
Pages: 750
Size: 8.25" wide x 10.50" long x 1.25" tall
Weight: 3.036
Language: English

The Purpose of Statistical Data Analysis
The Overall Goal of Statistical Data Analysis
Graphical and Numerical Descriptions of Data
Displaying Data as Distributions of Frequencies
Numerical Descriptions of Frequency Distributions
Linear Transformations of Scale and z-Scores
Modeling Data and the Estimation of Parameters
Imperfect Predictions, Models, and Residuals
Estimating the Parameters of a Model
Fitting Models with Categorical Predictor Variables
Probabilities Distributions
The Law of Large Numbers and the Meaning of Probability
Discrete Probability Distributions
The Central Limit Theorem and the Normal
Obtaining Probabilities for Normally Distributed Variables
The Normal Distribution as a Model for Residuals
Sampling Distributions and Interval Estimation
The Sampling Distribution of the Mean
Calculating Confidence Intervals
Interpreting Confidence Intervals
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
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
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
Experiments with Quantitative Predictor and Response Variables--Simple Linear Regression Examples
The Linear Model (Review)
Making Predictions
Assumptions and Factors Influencing Correlation and Regression
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
An Overview of Statistical Data Analysis
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