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The Essentials of Statistics A Tool for Social Research 4th Edition By Joseph F. Healey

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Pages: 482
File size: 24.21 MB
Format: Digital PDF
Course: Education
Category: eBook[PDF]

About this ebook

The Essentials of Statistics: A Tool for Social Research (4th Edition) by Joseph F. Healey is structured into three core domains tailored to develop statistical literacy in the social sciences: Descriptive Statistics, Inferential Statistics, and Bivariate Measures of Association. [1, 2, 3]

The detailed table of contents and topics covered across its 11 foundational chapters include: [1]

Chapter Overview & Foundational Concepts

Chapter 1: Introduction: Outlines the core role of statistics in scientific inquiry, the distinctions between discrete and continuous variables, and the fundamental differences between descriptive and inferential statistics. [1, 2]

Part I: Descriptive Statistics

Chapter 2: Basic Descriptive Statistics: Focuses on organizing data using tables, calculating percentages, ratios, and rates, and presenting findings visually through charts and graphs. [1, 2]
Chapter 3: Measures of Central Tendency: Explains how to find and interpret the center of a data distribution using the mode, median, and mean. [1]
Chapter 4: Measures of Dispersion: Demonstrates how to quantify variability or spread within data using techniques like range, interquartile range, variance, and standard deviation. [1]
Chapter 5: The Normal Curve: Covers the theoretical properties of the standard normal distribution (Z-scores) and how to calculate areas under the curve to interpret probabilities. [1]

Part II: Inferential Statistics

Chapter 6: Introduction to Inferential Statistics, the Sampling Distribution, and Estimation: Introduces logic regarding how samples represent populations, the Central Limit Theorem, and calculating confidence intervals.
Chapter 7: Hypothesis Testing I: The One-Sample Case: Steps through the basic logic of hypothesis testing by comparing a single sample mean or proportion to a known population parameter.
Chapter 8: Hypothesis Testing II: The Two-Sample Case: Focuses on testing significance between two independent sample means or proportions (such as comparing two demographic groups).
Chapter 9: Hypothesis Testing III: The Analysis of Variance (ANOVA): Explores testing for statistically significant differences across three or more separate sample groups.
Chapter 10: Hypothesis Testing IV: Chi-Square: Covers non-parametric hypothesis testing for nominal and ordinal variables to determine if a relationship exists between two categorical metrics. [1]

Part III: Bivariate Measures of Association

Chapter 11: Bivariate Association for Nominal- and Ordinal-Level Variables: Analyzes the strength and direction of relationships between variables using measures like Gamma, Lambda, and Phi. [1]