Essentials of Statistics for the Behavioral Sciences
by Frederick J Gravetter, Larry B. Wallnau, Lori-Ann B. Forzano
10th Edition
Publisher: Cengage Learning
Book Details
| Print ISBN | 9780357365298 |
| eText ISBN | 9798214343198 |
| Publisher | Cengage Learning |
| Publishing Year | 2021 |
| Edition | 10th Edition |
| Language | English |
| Pages | 608 |
Navigating the complex landscape of quantitative research requires more than just basic mathematical calculations. It demands a deep conceptual appreciation of how data translates into meaningful human insights. Essentials of Statistics for the Behavioral Sciences 10th Edition serves as a crucial bridge for students entering the social sciences, offering a clear roadmap through the often intimidating world of statistical analysis. By focusing on the logical foundations of each mathematical test, this textbook ensures that learners do not merely perform calculations in a vacuum. Instead, they develop the critical thinking skills necessary to interpret empirical findings in psychology, education, and related fields. In an era dominated by data-driven decision-making, mastering these analytical competencies is more vital than ever for aspiring researchers and practitioners.
The authors approach the subject with an admirable balance of rigor and accessibility. They systematically demystify complex procedures by breaking them down into manageable, sequential steps. Throughout the text, the coverage spans descriptive statistics, probability, hypothesis testing, t-tests, analysis of variance, correlation, and non-parametric tests. Rather than presenting these methods as isolated mathematical hurdles, the narrative frames them as tools for inquiry. This contextualized approach helps students understand the specific scenarios that warrant each test, transforming abstract equations into practical instruments for scientific discovery. By grounding theoretical concepts in real-world behavioral research, Essentials of Statistics for the Behavioral Sciences 10th Edition fosters a genuine appreciation for the scientific method and the empirical standards of the discipline.
Designed specifically for students who may possess a limited background in mathematics, this edition integrates intuitive learning aids and real-world examples. Distinctive features include step-by-step demonstrations, learning checks, and comprehensive summaries that reinforce key concepts before students move on to advanced material. Instructors and students alike will find that the Essentials of Statistics for the Behavioral Sciences 10th Edition PDF provides an invaluable digital companion, facilitating flexible study habits and seamless offline access. This updated volume remains the premier choice for undergraduate courses in behavioral statistics, successfully turning anxious students into confident, scientifically literate consumers of information.
Table of Contents
Chapter 1: Introduction to Statistics
- • Statistics, Science, and Observations
- • Variables and Measurement
- • Three Data Structures, Research Methods, and Statistics
- • Statistical Notation
Chapter 2: Frequency Distributions
- • Frequency Distribution Tables
- • Frequency Distribution Graphs
- • The Shape of a Frequency Distribution
- • Percentiles, Percentile Ranks, and Cumulative Limits
Chapter 3: Central Tendency
- • Overview of Central Tendency
- • The Mean
- • The Median
- • The Mode
- • Selecting a Measure of Central Tendency
Chapter 4: Variability
- • Introduction to Variability
- • Defining Range and Interquartile Range
- • Defining Variance and Standard Deviation
- • Calculating Variance and Standard Deviation for a Sample
Chapter 5: z-Scores: Location of Scores and Standardized Distributions
- • Introduction to z-Scores
- • z-Scores and Locations in a Distribution
- • Other Standardized Distributions Based on z-Scores
Chapter 6: Probability
- • Introduction to Probability
- • Probability and the Normal Distribution
- • Probabilities for Scores from a Normal Distribution
Chapter 7: Probability and Samples: The Distribution of Sample Means
- • Samples, Populations, and the Distribution of Sample Means
- • The Standard Error of M
- • Probability and the Distribution of Sample Means
Chapter 8: Introduction to Hypothesis Testing
- • The Logic of Hypothesis Testing
- • Uncertainty and Errors in Hypothesis Testing
- • An Example of a Hypothesis Test
- • Directional (One-Tailed) Hypothesis Tests
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
Chapter 10: The t Test for Two Independent Samples
- • The t Statistic for Two Independent Samples
- • Hypothesis Tests and Effect Size with the Independent-Measures t Statistic
- • Assumptions Underlying the Independent-Measures t Formula
Chapter 11: The t Test for Two Related Samples
- • The t Statistic for Two Related Samples
- • Hypothesis Tests and Effect Size for the Repeated-Measures Design
- • Comparing Repeated- and Independent-Measures Designs
Chapter 12: Introduction to Analysis of Variance (ANOVA)
- • Introduction to Analysis of Variance (ANOVA)
- • The Logic of ANOVA
- • ANOVA Notation and Formulas
- • Examples of Hypothesis Testing and Effect Size with ANOVA
Chapter 13: Two-Factor Analysis of Variance (Independent Measures)
- • Overview of the Two-Factor ANOVA
- • Notation and Formulas for Two-Factor ANOVA
- • Interpreting the Results of Two-Factor ANOVA
Chapter 14: Correlation and Regression
- • Introduction to Correlation
- • The Pearson Correlation
- • Understanding and Interpreting Correlation
- • Introduction to Linear Regression
Chapter 15: The Chi-Square Statistic: Tests for Goodness of Fit and Independence
- • Parametric and Nonparametric Statistical Tests
- • The Chi-Square Test for Goodness of Fit
- • The Chi-Square Test for Independence
- • Measuring Effect Size for Chi-Square
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