Statistics for Social Workers, 9th edition
- Robert W. Weinbach |
- Richard M. Grinnell |
Title overview
Invigorate learning with the Enhanced Pearson eText
The Enhanced Pearson eText provides a rich, interactive learning environment designed to improve student mastery of content with the following multimedia features:
- Embedded Flashcards. Readers can review key terms. (See page 44 and 82 for examples.)
- Chapter Review. Readers can check their understanding of chapter concepts by completing of chapter reviews. (See page 44 and 83 for examples.)
- Interactive Learning Objectives at the beginning of each chapter. (See page 1 and 65 for examples.)
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Additional text features include:
- Incorporates Real-life Examples - Major statistical tests presented throughout the text are accompanied by real-life examples. These examples show students how statistical analysis can be used in social work practice decision-making. New and revised case examples such as ethical considerations of central tendency and dispersion (Chapter 3), illustrate how statistical analysis can be used in day-to-day decision-making, as well as in basic research.
- De-emphasizes Mathematical Computations - Mathematical computations are de-emphasized, helping students to focus on understanding the importance of statistical analysis and apply the results to social work practice.
- Provides Visual Explanations - Numerous boxes, figures and tables summarize key sections and help students to comprehend some of the more abstract ideas presented.
- Addresses Ethical Issues - Potential ethical problems in the use of statistical analyses are identified, and suggestions are offered as to how they can be avoided.
- Connects Statistics and Research Design - The inter-relationship of statistics and research design is emphasized throughout, both in a new “Research Design” section in Chapter 1 and when each statistical test is discussed. The book describe how certain research designs and certain statistical analyses "go together."
Invigorate learning with the Enhanced Pearson eText
The Enhanced Pearson eText provides a rich, interactive learning environment designed to improve student mastery of content with the following multimedia features:
- Embedded Flashcards. Readers can review key terms. (See page 44 and 82 for examples.)
- Chapter Review. Readers can check their understanding of chapter concepts by completing of chapter reviews. (See page 44 and 83 for examples.)
- Interactive Learning Objectives at the beginning of each chapter. (See page 1 and 65 for examples.)
Instructors, visit pearsonhighered.com/etextbooks to register for your digital examination copy.
Key content changes include:
Correlated with the Council on Social Work Education (CSWE) Competencies.
Chapter 1
- Completely rewritten and reorganized
- A new section on research design
- Additional content on construction of dummy variables
- New content on the relationship between research hypotheses and statistics
- New content on null research findings and their value
- Increased emphasis on the use of statistics in descriptive research.
Chapter 2
- New content on computer generated graphs and the ethical issues they present
Chapter 3
- More content on measures of central tendency and dispersion, with new examples of how (ethically) to decide which to use
Chapter 4
- New content on sampling error and its relationship to research design
Chapter 5
- Increased emphasis on the role of the null hypothesis in statistics, and how the laws of probability are used
Chapter 6
- Content on sampling distributions has been re-organized and re-written for improved clarity.
Chapter 7
- A new section explaining the (often misunderstood) concept of degrees of freedom
- The various t-tests and ANOVA are now presented with a listing of the research designs with which each is most often used
Chapter 8
- New content on the meaning of each of the numbers in a cross-tabulation table
- More content on degrees of freedom and the various research designs where the chi-square test can be used
Chapter 9
- Correlation analysis is described as very versatile; it's use in both research design and hypothesis testing is described
- There are numerous new and previously used examples of how correlation can be misinterpreted if it is confused with causation
Chapter 10
- Examples of how regression analysis can be used for making everyday practice decisions
Chapter 11
- There is new and expanded description of meta-analysis with new examples
- A new box and a new figure support and clarify a new section on logic models and how they provide the focus for the statistical analysis that is used in different types of program evaluations
Table of contents
In this Section:
I) Brief Table of Contents
II) Detailed Table of Contents
I) Brief Table of Contents
Chapter 1. Introduction
Chapter 2. Frequency Distributions and Graphs
Chapter 3. Measures of Central Tendency and Variability
Chapter 4. Normal Distributions
Chapter 5. Testing Hypotheses
Chapter 6. Sampling Distributions
Chapter 7. t Tests and Analysis of Variance
Chapter 8. The Chi-Square Test of Association between Variables
Chapter 9. Correlation
Chapter 10. Regression
Chapter 11. Other Ways That Statistical Analyses Contribute to Evidence-Based Practice
II) Detailed Table of Contents
Chapter 1. Introduction
Useful Terms You Will Need to Know
Measurement iSSUES
Additional Measurement Classifications
Research Hypotheses
Classification of Variables and Their Relationship
Categories of Statistical Analyses
Statistics and data collection
Research designs and statistics
Chapter 2. Frequency Distributions and Graphs
Frequency Distributions
Grouped Frequency Distributions
Using Frequency Distributions to Analyze Data
Misrepresentation of Data
Graphs
A Caution: Computer-generated graphs
Chapter 3. Measures of Central Tendency and Variability
Measures of Central Tendency
Measures of Variability
Other Uses for Central Tendency and Variability
Chapter 4. Normal Distributions
Skewness
Kurtosis
The Normal Curve
The Standard Normal Distribution
Converting Raw Scores to z Scores and Percentiles
Deriving raw Scores From Percentiles
Chapter 5. Testing Hypotheses
Alternative Explanations for Relationships Within Samples
Probability and Inference
Refuting Sampling Error
Statistical Significance
Testing the Null Hypothesis
Errors in Drawing Conclusions About Relationships
Statistically Significant Relationships and Meaningful Findings
The Hypothesis Testing process
Chapter 6. Sampling Distributions
Sample Size and Sampling Error
What are Sampling Distribution?
Rejection Regions and hypothesis testing
Estimating Parameters
Selecting Statistical Tests
Deciding Which Test to use
Chapter 7. t Tests and Analysis of Variance
The use of t Tests
The One-sample t Test
The Dependent t Test
The Independent tTest
Misuse of t tests
Simple Analysis of Variance (Simple Anova)
Multivariate Analysis of Variance
Chapter 8. The Chi-Square Test of Association between Variables
When Chi-Square is Appropriate
Cross-Tabulation Tables
Using Chi-Square
When Chi-square is not appropriate
Using chi-square in social work practice
Cross-Tabulation With Three or More Variables
Special Applications of The Chi-Square Formula
Chapter 9. Correlation
Uses of Correlation
Scattergrams
Nonperfect Correlations
Interpreting Linear Correlations
Using Correlation for inference
Pearson’S r
Nonparametric Alternatives to Pearson’S r
Correlation With Three or More Variables
Other Multivariate analyses That use Correlation
Chapter 10. Regression
Prediction and Evidence-Based Practice
Prediction and Statistical Analysis
What is Simple Linear Regression?
Computation of the Regression Equation
More About the Regression Line
Interpreting Results
Using regression in social work practice
When is regression analysis appropriate
Regression With Three or More Variables
Other Types of Regression Analyses
Chapter 11. Other Ways That Statistical Analyses Contribute to Evidence-Based Practice
Meta-analyses
Program evaluations
Single-System designs
Author bios
Robert W. Weinbach, Ph.D., MSW, ACSW is Distinguished Professor Emeritus at the University of South Carolina, where he continues to teach graduate level research courses in the College of Social Work. He is also a co-author of Research Methods for Social Workers, seventh Edition; The Social Worker as Manager, Sixth Edition; and is the author of Evaluating Social Work Services and Programs, (all published by Allyn & Bacon), as well as over 75 other publications and invited book chapters. He earned graduate degrees in social work from SUNY-Buffalo and Ohio State University and has worked in both medical and psychiatric social work practice and as a program evaluator.
Richard M. Grinnell, Jr. is a Professor of Social Work and holds the Clair and Clarice Platt Jones/Helen Frays Endowed Chair of Social Work Research in the School of Social Work at Western Michigan University. He received his Ph.D. in social work from the University of Wisconsin at Madison and for over the past 40 years has held academic and senior university administrative appointments in Australia, Canada, and the United States. He has published over 100 journal articles, book chapters, and conference presentations, and 36 books. His two latest books are Evaluation for Social Workers: Foundations of Evidence–Based Programs, 6th edition (Oxford University Press, 2012, with Peter Gabor and Yvonne Unrau) and Social Work Research and Evaluation: Foundations of Evidence-Based Practice, 10th edition (Oxford University Press, 2014, with Yvonne Unrau).