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Statistics for Social Workers

Autor Robert W. Weinbach, Richard M. Jr. Grinnell
en Limba Engleză Paperback – 30 noi 2013
A reader-friendly approach to statistics in social work practice Statistics for Social Workers, 9/e familiarizes students with statistical tests and analyses that are most likely to be encountered by social work researchers and practitioners. This reader-friendly title emphasizes the conceptual underpinning of statistical analyses, keeping mathematics and complicated formulae to a minimum. Readers require no prior knowledge of statistics and only basic mathematical competence.
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Specificații

ISBN-13: 9780205867035
ISBN-10: 0205867030
Pagini: 285
Dimensiuni: 185 x 231 x 10 mm
Greutate: 0.39 kg
Ediția:9
Editura: Pearson

Cuprins

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