Statistics for The Behavioral Sciences
by Frederick J Gravetter, Larry B. Wallnau
10th Edition
Publisher: Cengage Learning
Book Details
| Print ISBN | 9781305504912 |
| eText ISBN | 9798214353272 |
| Publisher | Cengage Learning |
| Publishing Year | 2017 |
| Edition | 10th Edition |
| Language | English |
| Pages | 768 |
In an era dominated by data-driven decision-making, mastering quantitative analysis is no longer optional for students of human behavior. Statistics for the Behavioral Sciences 10th Edition serves as the definitive gateway to understanding how numerical observations translate into meaningful scientific discoveries. By demystifying complex mathematical formulas, this text empowers learners to look beyond raw data and grasp the underlying logical structures that define modern behavioral research. It addresses the common anxiety associated with statistics by framing the subject as a collection of tools designed to solve real-world puzzles rather than a series of abstract mathematical hurdles. Consequently, students learn how rigorous statistical design underpins the validity of psychological and sociological theories.
The authors establish a cohesive framework that spans descriptive statistics, probability theory, and advanced inferential methods. Rather than presenting calculations in a vacuum, the text contextualizes each procedure, explaining the historical and scientific necessity behind its development. From basic frequency distributions to multi-factor analysis of variance and non-parametric tests, students learn not just how to compute values, but when and why to apply specific statistical tools. In Statistics for the Behavioral Sciences 10th Edition, this conceptual approach ensures that readers build a robust foundation in scientific objectivity, preparing them to evaluate empirical claims critically in both academic settings and everyday life. By focusing on the logic behind the numbers, the text helps students transition from passive consumers of research to active, critical evaluators of scientific literature.
Designed primarily for undergraduate courses in psychology, sociology, and related social sciences, this edition integrates numerous learning checks, step-by-step demonstrations, and realistic end-of-chapter problems. Instructors worldwide adopt this textbook for its unmatched clarity, logical progression, and exceptional pedagogical support. For students seeking a flexible and portable learning solution, the Statistics for the Behavioral Sciences 10th Edition PDF provides instant access to these comprehensive resources across all digital devices. This digital format preserves the rich visual aids, detailed computational examples, and practical SPSS instructions that make the print version so effective. Ultimately, this edition serves as an indispensable companion for anyone looking to master the quantitative skills necessary for academic and professional success in the behavioral sciences.
Table of Contents
Chapter 1: Introduction to Statistics
- • Statistics, Science, and Observations
- • Data Structures, Research Methods, and Statistics
- • Variables and Measurement
- • Statistical Notation
Chapter 2: Frequency Distributions
- • Frequency Distributions and Frequency Distribution Tables
- • Grouped Frequency Distribution Tables
- • Frequency Distribution Graphs
- • Percentiles, Percentile Ranks, and Interpolation
- • Stem and Leaf Displays
Chapter 3: Central Tendency
- • Overview
- • The Mean
- • The Median
- • The Mode
- • Selecting a Measure of Central Tendency
- • Central Tendency and the Shape of the Distribution
Chapter 4: Variability
- • Introduction to Variability
- • Defining Standard Deviation and Variance
- • Measuring Variance and Standard Deviation for a Population
- • Measuring Standard Deviation and Variance for a Sample
- • Sample Variance as an Unbiased Statistic
Chapter 5: z-Scores: Location of Scores and Standardized Distributions
- • Introduction to z-Scores
- • z-Scores and Locations in a Distribution
- • Other Relationships Between z, X, μ, and σ
- • Using z-Scores to Standardize a Distribution
- • Computing z-Scores for Samples
Chapter 6: Probability
- • Introduction to Probability
- • Probability and the Normal Distribution
- • Probabilities and Proportions for Scores from a Normal Distribution
- • Probability and the Binomial Distribution
Chapter 7: Probability and Samples: The Distribution of Sample Means
- • Samples, Populations, and the Distribution of Sample Means
- • The Distribution of Sample Means for any Population and any Sample Size
- • Probability and the Distribution of Sample Means
- • More about Standard Error
Chapter 8: Introduction to Hypothesis Testing
- • The Logic of Hypothesis Testing
- • Uncertainty and Errors in Hypothesis Testing
- • Directional (One-Tailed) Hypothesis Tests
- • Concerns about Hypothesis Testing: Measuring Effect Size
- • Statistical Power
Chapter 9: Introduction to the t Statistic
- • 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
Chapter 10: The t Test for Two Independent Samples
- • Introduction to the Independent-Measures Design
- • The Null Hypothesis and the Independent-Measures t Statistic
- • Hypothesis Tests with the Independent-Measures t Statistic
- • Effect Size and Confidence Intervals for the Independent-Measures t
Chapter 11: The t Test for Two Related Samples
- • Introduction to Repeated-Measures Designs
- • The t Statistic for a Repeated-Measures Research Design
- • Hypothesis Tests for the Repeated-Measures Design
- • Effect Size and Confidence Intervals for the Repeated-Measures t
Chapter 12: Introduction to Analysis of Variance
- • Introduction (An Overview of Analysis of Variance)
- • The Logic of Analysis of Variance
- • ANOVA Notation and Formulas
- • Examples of Hypothesis Testing and Effect Size with ANOVA
- • Post Hoc Tests
Chapter 13: Repeated-Measures Analysis of Variance
- • Overview of the Repeated-Measures ANOVA
- • Hypothesis Testing and Effect Size with the Repeated-Measures ANOVA
- • More about the Repeated-Measures Design
Chapter 14: Two-Factor Analysis of Variance (Independent Measures)
- • An Overview of the Two-Factor, Independent-Measures, ANOVA: Main Effects and Interactions
- • An Example of the Two-Factor ANOVA and Effect Size
- • More about the Two-Factor ANOVA
Chapter 15: Correlation
- • Introduction
- • The Pearson Correlation
- • Using and Interpreting the Pearson Correlation
- • Hypothesis Tests with the Pearson Correlation
- • Alternatives to the Pearson Correlation
Chapter 16: Introduction to Regression
- • Introduction to Linear Equations and Regression
- • The Standard Error of Estimate and Analysis of Regression
- • Introduction to Multiple Regression with Two Predictor Variables
Chapter 17: The Chi-Square Statistic: Tests for Goodness of Fit and Independence
- • Introduction to Chi-Square: The Test for Goodness of Fit
- • An Example of the Chi-Square Test for Goodness of Fit
- • The Chi-Square Test for Independence
- • Effect Size and Assumptions for the Chi-Square Tests
Chapter 18: The Binomial Test
- • Introduction to the Binomial Test
- • An Example of the Binomial Test
- • More about the Binomial Test: Relationship with Chi-Square and the Sign Test
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- Statistics for The Behavioral Sciences by: Gravetter/Wallnau
- [PDF] Statistics for the Behavioral Sciences, 10th Edition
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- Statistics for the Behavioral Sciences 10th Edition - PubHTML5
- Statistics for The Behavioral Sciences (E-Book)
- Statistics for The Behavioral Sciences, 10th Edition - 9781305504912
- Statistics for Behavioral Sciences Textbook - Studylib
- [PDF] Statistics for the Behavioral Sciences, 10th Edition
- Statistics for The Behavioral Sciences
- Statistics for the behavioral sciences : Gravetter, Frederick J., author
- Statistics for the Behavioral Sciences 10th Edition - PubHTML5
- Statistics for the Behavioral Sciences | 9781305504912
- Statistics for the Behavioral Sciences - 10th Edition - Solutions and ...
