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Statistics for the Behavioral Sciences

Best in textbook rentals since 2012!

ISBN-10: 0495095206

ISBN-13: 9780495095200

Edition: 7th 2007

Authors: Frederick J. Gravetter, Larry B. Wallnau

List price: $183.95
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The best-selling introduction to statistics for students in the behavioral and social sciences, the Seventh Edition of STATISTICS FOR THE BEHAVIORAL SCIENCES continues to offer students straightforward instruction, accuracy, built-in learning aids, and real-world examples. Authors Frederick Gravetter and Larry Wallnau help students understand statistical procedures through a conceptual context that explains why the procedure was developed and when it should be used. The authors offer students numerous opportunities to practice statistical techniques through learning checks, examples, demonstrations, and problems. Instructors value the unparalleled ancillary package that accompanies this…    
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Book details

List price: $183.95
Edition: 7th
Copyright year: 2007
Publisher: Wadsworth
Publication date: 5/12/2006
Binding: Hardcover
Pages: 792
Size: 8.25" wide x 10.00" long x 1.25" tall
Weight: 3.388
Language: English

Frederick J Gravetter is Professor Emeritus of Psychology at The College at Brockport, State University of New York College. While teaching at Brockport, he specialized in statistics, research design, and cognitive psychology. Dr. Gravetter received his Bachelor's degree in mathematics from M.I.T. and his Ph.D. in psychology from Duke University. In addition to publishing several research articles, Dr. Gravetter is co-author of the best-selling STATISTICS FOR THE BEHAVIORAL SCIENCES, 9th Edition, ESSENTIALS OF STATISTICS FOR THE BEHAVIORAL SCIENCES, 8th Edition, and (with Lori-Ann B. Forzano) RESEARCH METHODS FOR THE BEHAVIORAL SCIENCES, 5th Edition.

Larry B. Wallnau is Professor Emeritus of Psychology at the State University of New York College at Brockport. The recipient of grants and awards in both research and teaching, Dr. Wallnau has published numerous research articles primarily on the effect of psychotropic drugs. With Frederick J Gravetter, he has co-authored previous editions of STATISTICS FOR THE BEHAVIORAL SCIENCES, now in its Ninth Edition, and ESSENTIALS OF STATISTICS FOR THE BEHAVIORAL SCIENCES, now in its Sixth Edition.

Introduction and Descriptive Statistics
Introduction to Statistics
Preview
Statistics, Science, and Observations
Populations and Samples
Data Structures, Research Methods, and Statistics
Variables and Measurement
Statistical Notation
Summary
Focus on Problem Solving
Demonstrations 1.1 and 1.2
Problems
Frequency Distributions
Preview
Overview
Frequency Distribution Tables
Frequency Distribution Graphs
The Shape of a Frequency Distribution
Percentiles, Percentile Ranks, and Interpolation
Stem and Leaf Displays
Summary
Focus on Problem Solving
Demonstrations 2.1 and 2.2
Problems
Central Tendency
Preview
Overview
The Mean
The Median
The Mode
Selecting a Measure of Central Tendency
Central Tendency and the Shape of the Distribution
Summary
Focus on Problem Solving
Demonstrations 3.1 and 3.2
Problems
Variability
Preview
Overview
The Range and Interquartile Range
Standard Deviation and Variance for a Population
Standard Deviation and Variance for Samples
More about Variance and Standard Deviation
Comparing Measures of Variability
Summary
Focus on Problem Solving
Demonstration 4.1
Problems
Foundations of Inferential Statistics
z-Scores: Location of Scores and Standardized Distributions
Preview
Introduction to z-Scores
z-Scores and Location in a Distribution
Using z-Scores to Standardize a Distribution
Other Standardized Distributions Based on z-Scores
Computing z-Scores for Samples
Looking Ahead to Inferential Statistics
Summary
Focus on Problem Solving
Demonstrations 5.1 and 5.2
Problems
Probability
Preview
Introduction to Probability
Probability and the Normal Distribution
Probabilities and Proportions for Scores from a Normal Distribution
Probability and the Binomial Distribution
Looking Ahead to Inferential Statistics
Summary
Focus on Problem Solving
Demonstrations 6.1 and 6.2
Problems
Probability and Samples: The Distribution of Sample Means
Preview
Overview
The Distribution of Sample Means
Probability and the Distribution of Sample Means
More about Standard Error
Looking Ahead to Inferential Statistics
Summary
Focus on Problem Solving
Demonstration 7.1
Problems
Inferences about Means and Mean Differences
Introduction to Hypothesis Testing
Preview
The Logic of Hypothesis Testing
Uncertainty and Errors in Hypothesis Testing
An Example of a Hypothesis Test
Directional (One-Tailed) Hypothesis Tests
The General Elements of Hypothesis Testing: A Review
Concerns about Hypothesis Testing: Measuring Effect Size
Statistical Power
Summary
Focus on Problem Solving
Demonstrations 8.1 and 8.2
Problems
Introduction to the t Statistic
Preview
The t Statistic-An Alternative to z
Hypothesis Tests with the t Statistic
Measuring Effect Size for the t Statistic
Directional Hypotheses and One-Tailed Tests
Summary
Focus on Problem Solving
Demonstrations 9.1 and 9.2
Problems
The t Test for Two Independent Samples
Preview
Overview
The t Statistic for an Independent-Measures Research Design
Hypothesis Tests and Effect Size with the Independent-Measures t Statistic
Assumptions Underlying the Independent-Measures t Formula
Summary
Focus on Problem Solving
Demonstrations 10.1 and 10.2
Problems
The t Test for Two Related Samples
Preview
Overview
The t Statistic for Related Samples
Hypothesis Tests and Effect Size for the Repeated-Measures Design
Uses and Assumptions for Related-Samples t Tests
Summary
Focus on Problem Solving
Demonstrations 11.1 and 11.2
Problems
Estimation
Preview
An Overview of Estimation
Estimation with the t Statistic
A Final Look at Estimation
Summary
Focus on Problem Solving
Demonstrations 12.1 and 12.2
Problems
Introduction to Analysis of Variance
Preview
Introduction
The Logic of Analysis of Variance
ANOVA Notation and Formulas
The Distribution of F-Ratios
Examples of Hypothesis Testing and Effect Size with ANOVA
Post Hoc Tests
The Relationship Between ANOVA and t Tests
Summary
Focus on Problem Solving
Demonstrations 13.1 and 13.2
Problems
Repeated-Measures Analysis of Variance (ANOVA)
Preview
Overview
Testing Hypotheses with the Repeated-Measures ANOVA
Advantages of the Repeated-Measures Design
Individual Differences and the Consistency of the Treatment Effects
Summary
Focus on Problem Solving
Demonstrations 14.1 and 14.2
Problems
Two-Factor Analysis of Variance (Independent Measures)
Preview
Overview
Main Effects and Interactions
Notation and Formulas
Interpreting the Results from a Two-Factor ANOVA
Assumptions for the Two-Factor ANOVA
Summary
Focus on Problem Solving
Demonstrations 15.1 and 15.2
Problems
Correlations and Nonparametric Tests
Correlation
Preview
Overview
The Pearson Correlation
Understanding and Interpreting the Pearson Correlation
Hypothesis Tests with the Pearson Correlation
The Spearman Correlation
Other Measures of Relationship
Summary
Focus on Problem Solving
Demonstrations 16.1 and 16.2
Problems
Introduction to Regression
Preview
Introduction to Linear Equations and Regression
Testing the Significance of the Regression Equation: Analysis of Regression
Introduction to Multiple Regression with Two Predictor Variables
Evaluating the Contribution of Each Predictor Variable
Summary
Focus on Problem Solving
Demonstrations 17.1 and 17.2
Problems
The Chi-Square Statistic: Tests for Goodness of Fit and Independence
Preview
Parametric and Nonparametric Statistical Tests
The Chi-Square Test for Goodness of Fit
The Chi-Square Test for Independence
Measuring Effect Size for the Chi-Square Test for Independence
Assumptions and Restrictions for Chi-Square Tests
Special Applications of the Chi-Square Tests
Summary
Focus on Problem Solving
Demonstration 18.1
Problems
The Binomial Test
Preview
Overview
The Binomial Test
The Relationship Between Chi-Square and the Binomial Test
The Sign Test
Summary
Focus on Problem Solving
Demonstration 19.1
Problems
Statistical Techniques for Ordinal Data: Mann-Whitney, Wilcoxon, Kruskal Wallis, and Friedman Tests
Preview
Data from an Ordinal Scale
The Mann-Whitney U-Test: An Alternative to the Independent-Measures t Test
The Wilcoxon Signed-Ranks Test: An Alternative to the Repeated-Measures t Test
The Kruskal-Wallis Test: An Alternative to the Independent-Measures ANOVA
The Friedman Test: An Alternative to Repeated-Measures ANOVA
Summary
Focus on Problem Solving
Demonstrations 20.1, 20.2, 20.3, and 20.4
Problems
Basic Mathematics Review
Symbols and Notation
Proportions: Fractions, Decimals, and Percentages
Negative Numbers
Basic Algebra: Solving Equations
Exponents and Square Roots
Statistical Tables
Solutions for Odd-Numbered Problems
General Instructions for Using SPSS
Statistics Organizer
References
Index
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