Statistics for Social Workers

Statistics for Social Workers, 9th edition

  • Robert W. Weinbach, 
  • Richard M. Grinnell

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Overview

Statistics for Social Workers helps you become familiar with statistical tests and analyses that you will likely encounter as a future social work researcher or practitioner. This reader-friendly title emphasizes the concepts behind statistical analyses while keeping mathematics and complicated formulae to a minimum.

Published by Pearson (February 13th 2014) - Copyright © 2015

ISBN-13: 9780205867257

Subject: Social Work & Human Services

Category: Research Methods in Social Work

Table of contents

In this Section:
I) Brief Table of Contents
II) Detailed Table of Contents

I) Brief Table of Contents

1. Introduction
2. Frequency Distributions and Graphs
3. Measures of Central Tendency and Variability
4. Normal Distributions
5. Testing Hypotheses
6. Sampling Distributions
7. t Tests and Analysis of Variance
8. The Chi-Square Test of Association between Variables
9. Correlation
10. Regression
11. Other Ways That Statistical Analyses Contribute to Evidence-Based Practice

II) Detailed Table of Contents

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

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

3. Measures of Central Tendency and Variability
Measures of Central Tendency
Measures of Variability
Other Uses for Central Tendency and Variability

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

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

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

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

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

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

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

11. Other Ways That Statistical Analyses Contribute to Evidence-Based Practice
Meta-analyses
Program evaluations
Single-System designs

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