Fundamental Statistics for the Behavioral Sciences

ISBN-10: 0840032978
ISBN-13: 9780840032973
Edition: 7th 2011
Authors: David C. Howell
List price: $191.95
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Book details

List price: $191.95
Edition: 7th
Copyright year: 2011
Publisher: Wadsworth
Publication date: 1/25/2010
Binding: Paperback
Pages: 672
Size: 7.00" wide x 9.25" long x 1.00" tall
Weight: 2.2
Language: English

David C. Howell is a professor emeritus and former chair of the psychology department at the University of Vermont. Professor Howell's primary area of research is in statistics and experimental methods. He is also the author of STATISTICS FOR THE BEHAVIORAL SCIENCES, currently in a Seventh Edition (Wadsworth, 2010), and the ENCYCLOPEDIA OF STATISTICS IN BEHAVIOR SCIENCE (2005) with Brian Everitt. Before retiring he frequently served as consultant with other faculty, both in the psychology department and in departments as disparate as Geology and Animal Sciences, and brings those experiences to this endeavor. Professor Howell's other interests include computing and the World Wide Web, and how technology affects communication, teaching, and research.

Introduction
The importance of Context
Basic Terminology
Selection among Statistical Procedures
Using Computers
Summary
Exercises
Basic Concepts
Scales of Measurement
Variables
Random Sampling
Notation
Summary
Exercises
Displaying Data
Plotting Data
Stem-and-Leaf Displays
Histograms
Reading Graphs
Alternative Methods of Plotting Data
Describing Distributions
Using Computer Programs to Display Data
Summary
Exercises
Measures of Central Tendency
The Mode
The Median
The Mean
Relative Advantages of the Mode, the Median, and the Mean
Obtaining Measures of Central Tendency Using SPSS
A Simple Demonstration-Seeing Statistics
Summary
Exercises
Measures of Variability
Range
Interquartile Range and Other Range Statistics
The Average Deviation
The Variance
The Standard Deviation
Computational Formulae for the Variance and the Standard eviation
The Mean and the Variance as Estimators
Boxplots: Graphical Representations of Dispersion and Extreme Scores
A Return to Trimming
Obtaining Measures of Dispersion Using SPSS
A Final Worked Example
Seeing Statistics
Summary
Exercises
The Normal Distribution
The Normal Distribution
The Standard Normal Distribution
Setting Probable Limits on an Observations
Measures Related to z
Seeing Statistics
Summary
Exercises
Basic Concepts of Probability
Probability
Basic Terminology and Rules
The Application of Probability to Controversial Issues
Writing Up the Results
Discrete versus Continuous Variables
Probability Distributions for Discrete Variables
Probability Distributions for Continuous Variables
Summary
Exercises
Sampling Distributions and Hypothesis Testing
Two Simple Examples Involving Course Evaluations and Rude Motorists
Sampling Distributions
Hypothesis Testing
The Null Hypothesis
Test Statistics and Their Sampling Distributions
Using the Normal Distribution to Test Hypotheses
Type I and Type II Errors
One- and Two-Tailed Tests
Seeing Statistics
A Final Worked Example
Back to Course Evaluations and Rude Motorists
Summary
Exercises
Correlation
Scatter Diagrams
The Relationship Between Pace of Life and Heart Disease
The Covariance
The Pearson Product-Moment Correlation Coefficient (r)
Correlations with Ranked Data
Factors that Affect the Correlation
Beware Extreme Observations
Correlation and Causation
If Something Looks Too Good to Be True, Perhaps It Is
Testing the Significance of a Correlation Coefficient
Intercorrelation Matrices
Other Correlation Coefficients
Using SPSS to Obtain Correlation Coefficients
Seeing Statistics
A Final Worked Example
Summary
Exercises
Regression
The Relationship Between Stress and Health
The Basic Data
The Regression Line
The Accuracy of Prediction
The Influence of Extreme Values
Hypothesis Testing in Regression
Computer Solutions using SPSS
Seeing Statistics
Summary
Exercises
Multiple Regression
Overview
A Different Data Set
Residuals
The Visual Representation of Multiple Regression
Hypothesis Testing
Refining the Regression Equation
A Second Example: Height and Weight
A Third Example: Psychological Symptoms in Cancer Patients
Summary
Exercises
Hypothesis Testing Applied to Means: One Sample
Sampling Distribution of the Mean
Testing Hypotheses about Means When ?? is Known
Testing a Sample Mean When ?? is Unknown (The One-Sample t)
Factors that Affect the Magnitude of t and the Decision about H0
A Second Example: The Moon Illusion
How Large is Our Effect?
Confidence Limits on the Mean
Using SPSS to Run One-Sample t tests
A Final Worked Example
Seeing Statistics
Summary
Exercises
Hypothesis Tests Applied to Means: Two Related Samples
Related Samples
Student's t Applied to Difference Scores
A Second Example: The Moon Illusion Again
Advantages and Disadvantages of Using Related Samples
How Large an Effect Have We Found?
Confidence Limits on Changes
Using SPSS for t Tests on Related Samples
Writing Up the Results
Summary
Exercises
Hypothesis Tests Applied to Means: Two Independent Samples
Distribution of Differences Between Means
Heterogeneity of Variance
Nonnormality of Distributions
A Second Example with Two Independent Samples
Effect Sizes Again
Confidence Limits on ??1 ?V ??2
Writing Up the Results
Use of Computer Programs for Analysis of Two Independent Sample Means
A Final Worked Example
Seeing Statistics
Summary
Exercises
Power
The Basic Concept
Factors that Affect the Power of a Test
Effect Size
Power Calculations for the One-Sample t Test
Power Calculations for Differences Between Two Independent Means
Power Calculations for the t Test for Related Samples
Power Considerations in Terms of Sample Size
You Don't Have to Do It by Hand
Seeing Statistics
Summary
Exercises
One-Way Analysis of Variance
The General Approach
The Logic of the Analysis of Variance
Calculations for the Analysis of Variances
Unequal Sample Sizes
Multiple Comparison Procedures
Violations of Assumptions
The Size of the Effects
Writing Up the Results
The Use of SPSS for a One-Way Analysis of Variance
A Final Worked Example
Seeing Statistics
Summary
Exercises
Factorial Analysis of Variance Factorial Designs
The Extension of the Eysenck Study
Interactions
Simple Effects
Measures of Association and Effect Size
Reporting the Results
Unequal Sample Sizes
A Second Example: Maternal Adaptation Revisited
Using SPSS for Factorial Analysis of Variance
Seeing Statistics
Summary
Exercises
Repeated-Measures Analysis of Variance
An Example: Depression as a Response to an Earthquake
Multiple Comparisons
Effect Size
Assumptions involved in Repeated-Measures Designs
Advantages and Disadvantages of Repeated-Measures Designs
Using SPSS to Analyze Data in a Repeated-Measures Design
Writing Up the Results
A Final Worked Example
Summary
Exercises
Chi-Square
One Classification Variable: The Chi-Square Goodness of Fit Test
Two Classification Variables: Analysis of Contingency Tables
Possible Improvements on Standard Chi-Square
Chi-Square for Larger Contingency Tables
The Problem of Small Expected Frequencies
The Use of Chi-Square as a Test of Proportions
Nonindependent Observations
SPSS Analysis of Contingency Tables
Measures of Effect Size
A Final Worked Example
Writing Up the Results
Seeing Statistics
Summary
Exercises
Nonparametric and Distribution-Free Statistical Tests
The Mann-Whitney Test
Wilcoxon's Matched-Pairs Signed-Ranks Test
Kruskal-Wallis One-Way Analysis of Variance
Friedman's Rank Test for k Correlated Samples
Measures of Effect Size
Writing Up the Results
Summary
Exercises
Choosing the Appropriate Analysis
Exercises and Examples
Arithmetic Review
Symbols and Notation
Basic Statistical Formulae
Dataset
Statistical Tables
Glossary
References
Answers to Selected Exercises
Index

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