Syllabus Social Work 596: Introduction to Statistics for Social Work Practitioners

Instructor:                                                                                Andrea Doyle

Gunnar Almgren                                                                      adoyle@u.washington.edu

Office 127L                                                                            

Phone 685-4077                                                         

e-mail mukboy@u.washington.edu

http://faculty.washington.edu/mukboy/home/almgren.htm 

Lectures Schedule/Location: All lectures/homework sessions in SSW 305 from 5:00 PM to 10:00 PM on the following days:

9/8 Monday, 9/10 Wednesday, 9/11 Thursday

9/15 Monday, 9/17 Wednesday

Final Exam Monday 9/22 at 6:00 PM SSW 305

Course Description

This course is designed to fulfill an acceptable statistics prerequisite for the foundation year research courses in the MSW program, Social  Work 505 and Social Work 506. The course provides an introductory foundation in descriptive statistics, probability theory, statistical inference, and bivariate statistics that are commonly used in evaluations of social programs and in the evaluation of clinical practice. The approach of this course is basically conceptual, with heavy emphasis on the understanding of the logic of measurement and statistical inference. While the content is primarily conceptual, understanding of many of the critical concepts is best served by doing some hand calculation that involves use of high school level algebra.

General Objectives for the Course

By the end of the first quarter, students will:

1. Understand the basic properties of descriptive statistics and inferential statistics, and their application to program evaluation and empirical practice.

2. Be able to identify, calculate, and interpret statistics that describe basic properties of distributions and relationships between two variables.

3. Understand the logic of statistical hypothesis testing, the types of errors that can be made, and the risks and trade-offs that are implicit within the hypothesis testing process.

4. Understand the components, calculation, application, and interpretation of basic inferential statistics to the analysis of relationships between variables.

5. Be able to construct basic statistical tables and interpret common graphical interpretations of data.

6. Understand the interdependent relationship between qualitative and quantitative methods in the development of a professional knowledge base.

7. Understand some common errors in statistical reasoning and misapplication of methods, as well as ways in which statistical methods can be used to either distort or inform understanding. 

Course Format

1. The class will be offered in a series of five 3 hour lecture sessions, supported by 2 hour problem set labs offered twice weekly by the teaching assistant.

2. Problem sets are assigned for each class session, to be turned in to the teaching assistant by the following class session. Completion of problem set assignments in most cases is essential to the mastery of concepts and exam preparation.

3. Students will take a final exam on the main statistical concepts taught in the class.

4. The course will be pass/fail, with assigned problem sets counting as 25% of the course grade and a final exam counting as 75%.

Required Texts:

Examining Global Social Welfare Issues Using MicroCase

Andrew L. Cherry

ISBN: 0534610382

Essentials of Statistics for the Behavioral Sciences

Frederick J. Gravetter, Larry B. Wallnau

ISBN: 0534586171

Other Readings:

Gunnar Almgren. “Statistics for Human Service Workers”. In (Albert Roberts and Kenneth Yeager eds.) Handbook of Practice Based Research. (2003) New York: Oxford University Press.

Class Schedule

Session I

Monday September 8^th 5 PM to 8 PM

Problem Set Lab 8 PM -10 PM

General Introduction

Levels of Measurement

Describing Frequency Distributions

Measures of Central Tendency and Dispersion

Session II

Wednesday September 10^th 5 PM to 8 PM

Problem Set Lab 8 PM -10 PM

Probability and Statistical Inference

            Essential Rules of Probability

            Distributions Employed in Statistical Inference

            The Central Limit Theorem and Extensions of the CLT

Session III

Thursday September 11^th 5 PM to 8 PM

Problem Set Lab 8 PM -10 PM

Conventional Approaches to Hypothesis Testing

            Type I and Type II Errors

            Directional and Non-Directional Tests

            The One Sample t-Test and Confidence Intervals

Session IV

Monday September 15^th 5 PM to 8 PM

Problem Set Lab 8 PM -10 PM

            Between vs. Within Subjects Designs and Statistical Implications

            Analysis of Bivariate Relationships: Nominal Level Data    

            Independent Samples t-Tests

Session V

Wednesday September 17^th 5 PM to 8 PM

Problem Set Lab 8 PM -10 PM

One-Way ANOVA: Between Measures

Bivariate Correlation and Regression

Exam Monday September 22, 6 PM