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Instructor Class Description

Time Schedule:

Elizabeth A. Wells
SOC WL 587
Seattle Campus

Fundamentals of Social Work Statistics I

Descriptive and inferential statistics. Underlying logic of statistical inference. Statistical issues of special relevance in social work, including measurement, research design, and ethics in research. Prerequisite: concurrent registration in SOC WL 580. Offered: A.

Class description

SWL 587 is the first of a two-quarter required sequence in statistics for social welfare research that is offered to first year Ph.D. students. The primary objective of the sequence is to provide a basic foundation in univariate descriptive statistics, probability theory, bivariate descriptive statistics, bivariate inferential statistics, and an introduction to multivariate regression, analysis of variance and analysis of covariance. The laboratory session is used to gain competence in using the statistical software, SPSS, to conduct data analyses. In addition, students will gain a fundamental understanding of the place, potential, and limitations of statistical analysis in social work and social welfare research. The perspective from which this course is taught is that the statistical analysis of social issues and problems involves the responsible application of a set of mathematical concepts and tools in pursuit of ways to improve the human condition. Content will include ethical issues concerning the appropriate application, interpretation, and use of social research, as well as the potential limitations and biases of applications that fail to adequately consider issues of population diversity.

The approach of this course is basically conceptual, with heavy emphasis on the understanding of the logic of measurement and statistical inference. Although the content includes the use of computer applications for the management of data and calculation of specific statistics, understanding of many of the critical concepts is best served by doing some hand calculations that involve use of algebra. A foundation in basic algebra is sufficient but essential preparation for this course.

General Objectives for the Course

By the end of the first quarter, students will

1. Understand and be able to describe the general applications of descriptive statistics and inferential statistics, and know the difference between these two types of statistics.

2. Understand and be able to apply basic descriptive statistics to data in a manner that is consistent with scholarly convention. This includes the capacity to identify, calculate, and interpret the appropriate statistic across a wide variety of examples and data situations.

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 two variables.

5. Distinguish between statistical significance and clinical or practical significance, and calculate and interpret measures of strength of association or effect size.

6. Be able to use the personal computer version of SPSS to manage data and compute basic descriptive and inferential statistics, both to describe the relevant statistical characteristics of samples and to test hypotheses about associations among variables. This involves both the identification of appropriate procedures and interpretation of computer output.

7. Understand some of the ways in which statistics can be misused in social welfare research in a manner that perpetuates oppression and social disadvantage.

8. Develop a philosophy of honest and ethical use of statistics and reporting of research results.

Student learning goals

General method of instruction

1. Lectures will occur two days per week and will follow the textbook fairly closely. Weekly textbook and other readings need to be read before class to promote mastery of the material. The teaching assistant (TA) will hold optional study and review sessions throughout the quarter.

2. Homework problems are assigned each week, to be completed and turned in to your TA by class time Monday of the week following the assignment. Completion of homework assignments is essential to the mastery of concepts and exam preparation.

3. A weekly computer lab will be held to teach and enhance the ability to conduct and interpret computer applications of statistical analysis. We will use SPSS-PC for Windows, available on the School of Social Work LAN. All lab assignments are to be handed in to your TA by class time Monday of the week following the assignment. Assignments are indicated on a separate handout distributed the first day of lab.

Learning Goals for Lab:

a. Students are comfortable with using SPSS for analysis. b. Students are able to use window commands to run statistical procedures learned in class. c. Students gain a working familiarity with use of syntax in SPSS. d. Students are able to select appropriate SPSS commands for a given analysis. e. Students are able to interpret output from analysis and to explain results both verbally and in writing.

5.

Recommended preparation

Class assignments and grading

Gravetter, F. J. and Wallnau, L. B. (2007), Statistics for the Behavioral Sciences 7th Ed. Belmont CA: Wadsworth.

PART I: REVIEW OF BASICS

Week 1 Sept. 27: Introductions and overview of class, basic concepts, ethics in research,

A. Required readings: 1. Text: Read Chapters 1 & 2 2. NASW Code of Research Ethics [Although section 5.02 deals specifically with research issues, many other parts of the code are relevant to social work and social welfare research and the responsibilities of social workers conducting research. I urge you to read this code in its entirety.] 3. Blanck, P. D., Bellack, A. S., Rosnow, R. L., Rotheram-Borus, M. J., & Schooler, N.I. (1992). Scientific rewards and conflicts of ethical choices in human subjects research. American Psychologist, 47, 959 – 965. 4. American Psychological Association Publication Manual (2001). Avoiding bias in language. [Please read by end of quarter, but not necessary to read this first week of class.]

Recommended reading: Rosnow, R.L. (1997) Hedgehogs, foxes, and the evolving social contract in psychological science: Ethical challenges and methodological opportunities. Psychological Methods, 2(4), 345-356.

Acock, A.C. (2005). SAS, Stata, SPSS: A Comparison. Journal of Marriage and Family. 67(4) 1093-1095.

B. Homework due 10/2. Chap. 1, Problems #2, 3, 4, 8, 9, 14, 18, 21

C. Lab assignment for each week on separate handout

Week 2 Oct. 2: Frequency distributions. Oct. 4: Measures of central tendency

A. Required reading: Text Chap. 3 Chap. 4

B. Homework due 10/9. Chap. 2, Problems #1, 9, 18, 20 Chap. 3, Problems #2, 3, 4, 6, 11, 14, 22

Week 3 Oct.9: Measures of variability Oct. 11: z-scores and standardized distributions

A. Required reading: Text Chap. 5 Chap. 6 B. Homework due 10/16 Chap. 4, Problems # 1, 3, 4, 6, 17, 21, 22 Chap. 5, Problems # 1, 3, 4, 5, 6, 23

Week 4 Oct. 16: Introduction to probability theory and normal distributions Oct. 18: Binomial distributions

A. Required reading Howell, D.C. (2002). Basic concepts of probability. Chapter 5 in Howell, D.C., Statistical Methods for Psychology, 5th Ed., Pacific Grove, CA: Wadsworth.

B. Homework due 10/23: Chap. 6, Problems #1, 2, 3, 5, 8b, 11c, 15, 23a & c, 26, 27. Howell, Chap. 5, Problems 5.2, 5.3, 5.8, 5.25, 5.24, 5.26,

PART II: STATISTICAL INFERENCE

Week 5 Oct. 23: Quiz 1 Oct. 25: Sampling distribution of the mean e

A. Required reading Text: Chap. 7 Chap. 8 Weinbach, R. W. (1989) When is a statistical test meaningful? A practical perspective. Journal of Sociology and Social Welfare, 16 (1): 31 – 37.

Recommended reading Rosenthal, J.A. (1997). Pragmatic concepts and tools for data interpretation: A balanced model. Journal of Teaching in Social Work, 15, 113-130.

B. Homework due 10/30: Chap. 7, Problems #1, 2, 4, 6, 8, 9, 14, 21, 23

Week 6 Oct. 30: Hypothesis Testing, Type I and Type II Errors, 1- vs. 2-tailed Tests, Effect Size Nov. 1 Power of a Statistical Test

A. Required reading Text Chap. 18 (Skip Section 18.6)

Orme, J. G. & Combs-Orme, T. D. (1986). Statistical power and Type II errors in social work research. Social Work Research & Abstracts, 22(3), pp. 3 – 10. Recommended reading (application of ÷2 test in research)

Agree, E. N. & Freedman, V. A. (2003). A comparison of assistive technology and personal care in alleviating disability and unmet need. The Gerontologist, 43, 335 – 344.

B. Homework due 11/6: Chap. 8, Problems #1, 2, 3, 5, 6, 8, 11, 14, 17, 26, 27

Week 7 Nov. 6: Chi Square goodness of fit test and test of independence Nov. 8: Single sample t-test

A. Required reading: Text, Chap. 9 Chap. 11

Recommended reading (application of t-test in research):

Nash, J. K., Fraser, M. W., Galinsky, M. J., Kupper, L. L. (2003). Early development and pilot testing of a problem-solving skills-training program for children. Research on Social Work Practice, 13, 432 – 450.

B. Homework due 11/13: Chap. 18, Problems # 6, 7, 17, 18 Chap. 9, Problems #1, 2, 3, 4, 5, 7, 11, 15

Week 8 Nov. 13: t-test for related (correlated) samples Nov. 15: Quiz 2

A. Required reading: Text Chap. 10 Chap. 12

Recommended reading (application of t-test in research):

Mazur, M. A. & Emmers-Sommer, T. M. (2002). The effect of movie portrayals on audience attitudes about nontraditional families and sexual orientation. Journal of Homosexuality, 44, 157 – 174.

B. Homework due 11/20: Chap. 11, Problems #1, 5, 7, 8, 10, 13, 17, 18, 19

Week 9 Nov. 20: t-test for independent groups, confidence intervals Nov. 22: 1-way analysis of variance for independent groups (ANOVA)

A. Required Reading Text Chap 13

Recommended reading (application of 1-way ANOVA):

Conley, T. D., Devine, P. G., Rabow, J., & Evett, S. R. (2002). Gay men and lesbians’ experiences in and expectations for interactions wth heterosexuals. Journal of Homosexuality, 44, 83 – 109.

B. Homework due 11/27: Chap. 10, Problems #1, 2, 3, 4, 5, 9, 14, 15 Chap. 12, Problems #3, 6, 12 Chap. 13, Problems #1, 2, 3, 4, 10, 21, 24

Week 10 Nov. 27: Post Hoc Tests Nov. 29: 1-Way repeated measures analysis of variance

A. Required reading: Text Chap. 14

B. Homework due 12/4: Chap. 13, Problem # 25 Chap. 14, Problems #1, 3, 4, 5, 12, 16, 20, 22

Week 11 Dec. 4: ANOVA continued, course evaluations Dec. 6: Final exam

Note: There will be no lab or homework for the last week.

There will be two midterm quizzes and a final exam. These exams are in class “open book” and “open notes” and test the student’s ability to apply what has been learned through lectures, reading, and completing the homework assignments. The exams will be cumulative because the concepts taught in the course are progressive in nature. Preparation for a cumulative exam is more likely to promote long term mastery of key concepts. The final examination is scheduled for Wednesday, Dec. 6

6. The final grade for the course will be based on all aspects of course work. Homework = 20%; laboratory assignments = 10%; midterm quiz 1 = 15%; midterm quiz 2 = 25%; final exam = 30%.


The information above is intended to be helpful in choosing courses. Because the instructor may further develop his/her plans for this course, its characteristics are subject to change without notice. In most cases, the official course syllabus will be distributed on the first day of class.
Last Update by Elizabeth A. Wells
Date: 09/11/2006