Statistics for Social Workers / Edition 8

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Overview

Now in its eighth edition, this widely used text covers the types of statistical analyses that are most likely to be encountered by social work practitioners and researchers. It requires no prior knowledge of statistics and only basic mathematical competence.
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Editorial Reviews

Booknews
Written for undergraduate or graduate social work students and practitioners without an extensive mathematical background, this text focuses on the core processes of statistics. Changes to this edition mostly consist of substantial reorganization, expanded coverage of logistic regression and tests, and the addition of some figures. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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Product Details

  • ISBN-13: 9780205739875
  • Publisher: Pearson
  • Publication date: 8/5/2009
  • Series: MySearchLab Series 15% off Series
  • Edition description: Older Edition
  • Edition number: 8
  • Pages: 312
  • Sales rank: 133,177
  • Product dimensions: 6.90 (w) x 9.10 (h) x 0.40 (d)

Meet the Author

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).

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Table of Contents

Preface

1 Introduction
USE OF STATISTICS
METHODOLOGICAL TERMS

Data
Information
Variables and Constants
Conceptualization
Operationalization
Reliability
Validity

RESEARCH HYPOTHESES
Three Forms of Research Hypotheses
Causal and Non-causal Research Hypotheses
Independent and Dependent Variables

MEASUREMENT LEVELS
Nominal
Ordinal
Interval
Ratio

MEASUREMENT LEVELS AND DATA ANALYSIS
ADDITIONAL MEASUREMENT CLASSIFICATIONS
Discrete and Continuous Variables
Dichotomous, Binary, and Dummy Variables

CATEGORIES OF STATISTICAL ANALYSES
Number of Variables in an Analysis
Primary Purpose of the Analysis

CONCLUDING THOUGHTS
STUDY QUESTIONS

2 Frequency Distributions and Graphs
FREQUENCY DISTRIBUTIONS

Absolute Frequency Distributions
Cumulative Frequency Distributions
Percentage Frequency Distributions
Cumulative Percentage Frequency Distributions

GROUPED FREQUENCY DISTRIBUTIONS
USING FREQUENCY DISTRIBUTIONS TO ANALYZE DATA
MISREPRESENTATION OF DATA
GRAPHS
Bar Graphs and Line Diagrams
Pie Charts
Histograms
Frequency Polygons
Stem-and-Leaf Plots

A COMMON MISTAKE IN DISPLAYING DATA
CONCLUDING THOUGHTS
STUDY QUESTIONS

3 Measures of Central Tendency and Variability
MEASURES OF CENTRAL TENDENCY

The Mode
The Median
The Mean
Which Measure of Central Tendency to Use?

MEASURES OF VARIABILITY
The Range
The Interquartile Range
The Mean Deviation
Variance
Standard Deviation
Reporting Measures of Variability

OTHER USES FOR CENTRAL TENDENCY AND VARIABILITY
CONCLUDING THOUGHTS
STUDY QUESTIONS

4 Normal Distributions
SKEWNESS
KURTOSIS
NORMAL DISTRIBUTIONS
CONVERTING RAW SCORES TO Z SCORES AND PERCENTILES

Practical Uses of z Scores

DERIVING RAW SCORES FROM PERCENTILES
CONCLUDING THOUGHTS
STUDY QUESTIONS

5 Hypothesis Testing: Basic Principles
ALTERNATIVE EXPLANATIONS FOR RELATIONSHIPS WITHIN SAMPLES

Rival Hypotheses
Research Design Flaws
Sampling Error

PROBABILITY AND INFERENCE
REFUTING SAMPLING ERROR
Replication
Statistical Analyses

STATISTICAL SIGNIFICANCE
p values
Rejection Levels (Alpha)

ERRORS IN DRAWING CONCLUSIONS ABOUT RELATIONSHIPS
Avoiding Type I Errors
Avoiding Type II Errors

STATISTICALLY SIGNIFICANT RELATIONSHIPS AND MEANINGFUL FINDINGS
More about Effect Size
Is the Relationship Valuable?
Complex Interpretations of Statistically Significant Relationships

THE PROCESS OF HYPOTHESIS TESTING
CONCLUDING THOUGHTS
STUDY QUESTIONS

6 Sampling Distributions, Rejection Regions, and Statistical Test Selection

SAMPLE SIZE AND SAMPLING ERROR
SAMPLING DISTRIBUTIONS AND INFERENCE

Comparing an Experimental Sample with Its Population
Comparing a Non-Experimental Sample with Its Population

SAMPLING DISTRIBUTION OF MEANS
Samples Drawn from Normal Distributions
Samples Drawn from Skewed Distributions

ESTIMATING PARAMETERS
Constructing a 95 Percent Confidence Interval
Constructing a 99 Percent Confidence Interval

SELECTING A STATISTICAL TEST
The Importance of Selecting the Correct Test
Factors to Consider in Selecting the Correct Test

PARAMETRIC AND NONPARAMETRIC TESTS
MULTIVARIATE TESTS
DECIDING WHICH TEST TO USE
More about Getting Help

CONCLUDING THOUGHTS
STUDY QUESTIONS

7 t Tests and Analysis of Variance
THE USE OF t TESTS

Misuse of t

THE ONE-SAMPLE t TEST
Determining If a Sample Is Representative
Seeking Support for a Research Hypothesis
Presentation of Findings
A Nonparametric Alternative: Chi-Square Goodness of Fit

THE DEPENDENT t TEST
Use with Two Connected (or Matched) Samples Measured Once
Use with One Sample Measured Twice
A Nonparametric Alternative: Wilcoxon Sign

THE INDEPENDENT t TEST
Nonparametric Alternatives: U and K-S
A Multivariate Alternative: T2

SIMPLE ANALYSIS OF VARIANCE (SIMPLE ANOVA)
Additional Data Analyses
A Nonparametric Alternative: Kruskal-Wallis

MULTIVARIATE ANALYSIS OF VARIANCE
CONCLUDING THOUGHTS
STUDY QUESTIONS

8 The Chi-square Test of Association Between Variables
WHEN CHI-SQUARE IS APPROPRIATE
CROSS-TABULATION TABLES

Degrees of Freedom
Using Chi-Square
Presentation of Findings
Interpreting the Results of a Chi-Square Analysis
Meaningfulness and Sample Size
Restrictions on the Use of Chi-Square
An Alternative: Fisher’s Exact Test
Using Chi-Square in Social Work Practice

CROSS TABULATION WITH THREE OR MORE VARIABLES
Problems with Sizes of Expected Frequencies
Effects of Introducing Additional Variables

SPECIAL APPLICATIONS OF THE CHI-SQUARE FORMULA
McNemar’s Test
The Median Test

CONCLUDING THOUGHTS
STUDY QUESTIONS

9 Correlation Analyses
USES OF CORRELATION
SCATTERGRAMS
PERFECT CORRELATIONS
NONPERFECT CORRELATIONS
INTERPRETING LINEAR CORRELATIONS

Understanding Correlation Coefficients
Very Strong Correlations
Remember,Correlation Is Not Causation!
Using Correlation For Inference

PEARSON’S r
Computation and Presentation

NONPARAMETRIC ALTERNATIVES
Spearman’s Rho and Kendall’s Tau

CORRELATION WITH THREE OR MORE VARIABLES
Partial r
Multiple R
Variations of Multiple R

OTHER MULTIVARIATE TESTS THAT USE CORRELATION
Factor Analysis
Cluster Analysis

CONCLUDING THOUGHTS
STUDY QUESTIONS

10 Regression Analyses
PREDICTION AND EVIDENCE BASED PRACTICE
PREDICTION AND STATISTICAL ANALYSIS
WHAT IS SIMPLE LINEAR REGRESSION?

Research Questions in Simple Linear Regression
Limitations of Simple Linear Regression

COMPUTATION OF THE REGRESSION EQUATION
MORE ABOUT THE REGRESSION LINE
The Least-Squares Criterion
Interchanging X and Y Variables

INTERPRETING RESULTS
Presentation of Y ?
The Standard Error
Using Regression in Social Work Practice

REGRESSION WITH THREE OR MORE VARIABLES
Options for Entering Variables

OTHER TYPES OF REGRESSION ANALYSES
Discriminant Analysis
Logistic Regression

CONCLUDING THOUGHTS
STUDY QUESTIONS

11Other Ways that Statistical Analyses Contribute to Evidence-Based Practice
META-ANALYSIS
ANSWERS SOUGHT IN PROGRAM EVALUATIONS
NEEDS ASSESSMENTS AND FORMATIVE EVALUATIONS
OUTCOME EVALUATIONS

Hypothesis Testing in Outcome Evaluations
Statistical Analyses of Outcome Evaluation Data

ANSWERS SOUGHT IN SINGLE-SYSTEM RESEARCH
Hypothesis Testing in Single-System Research
Statistical Analyses of Single-System Data
Using Familiar Statistical Tests
Two Other Popular Tests

CONCLUDING THOUGHTS
STUDY QUESTIONS
Appendix A Beginning to Select a Statistical Test
Glossary
Index
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