Download Statistics - University of Arkansas at Little Rock

University of Arkansas at Little Rock
School of Social Work
Course Outline
Course: SOWK 8371
Pre-requisite: Social Work Methods of Research
Title: Statistics for Social Work
Semester Credits: 3
Instructors: Lloyd, Turturro, Tripathi.
I. COURSE DESCRIPTION
This course is an introduction to statistics and their use in analyzing data. In particular, it is an
introduction and/or review of probability, inferential, and decision-making statistics. Emphasis
will be placed on the application of critical thinking to inform and communicate professional
judgments (advanced competency #3). The course covers basic statistics, including central
tendencies (e.g., mean, mode), variability (e.g., standard deviation), data distributions (e.g.,
normal, nonparametric); bivariate and multivariate procedures. The course also involves
critiquing empirical research articles in social work journals, building on knowledge of
methodology learned in the first course of research and developing new knowledge of statistical
methods, in order to engage in research-informed practice and practice-informed research as
social work practitioners (advanced competency #6). The course is designed to teach students
statistics applicable to practice, including how statistics are used in determining needs and
making agencies more responsive to these needs. The values and ethics involved in the use of
statistics are taught, with particular emphasis on regard for individual worth and dignity, as well
as self-determination in research. Emphasis is also placed on use of statistics in regard to issues
of diversity, social and economic justice, diversity, and quality of practice in general. At the
concentration level, advanced practitioners, in working with individuals, families, groups, and
organizations, will learn to apply statistical procedures in the evaluation of the effects of
interventions and to modify strategies based on client outcome (advanced competency #10)
II. COURSE OBJECTIVES
1) Students will demonstrate on exams and written assignments knowledge of probability
theory, data distributions, various statistical procedures, and statistical inferences based on
social work values and ethical issues (content for advanced competency #6 for ADP and MCP).
2) Students will demonstrate in written assignments that they understand how to apply
assumptions of statistical procedures (content for advanced competency #6 for ADP and MCP).
3) Students will demonstrate on exams and in written assignments that they can choose the
appropriate analyses for various issues, including the ability to assess results of evaluation
and modify treatment goals as needed ( practice behavior ADP10.8 for advanced competency #10), the
ability to critically analyze, monitor, and evaluate their own practice interventions (MCP
practice behavior 10.10 for advanced competency #10), and the ability to critically analyze, monitor,
and evaluate the effectiveness of social welfare programs (MCP practice behavior 10.11 for
advanced competency 10).
4) Students will demonstrate in written assignments, critiques of professional research
articles, and the final assessment that they can apply statistics to social work practice, and,
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with client systems, evaluate, select, and use effective evidence-based intervention strategies
in working with individuals, families, groups, and organizations (MCP practice behavior 3.1 for
advanced competency #3 and ADP practice behavior 6.1 for advanced competency #6).
5) Students will demonstrate through critiques of professional research articles and in written
assignments that they can apply statistics with regard to individual worth, dignity, needs,
diversity, and self-determination (content for advanced competency #4).
6) Students will demonstrate through critiques of professional research articles and in written
assignments that they can assess the overall methodology of research studies. They will
assess in writing problem statements (conceptualization), sampling, design, measurement,
procedures, analyses, interpretation, values, ethics, and generalization, with emphasis on
making institutions more responsive to needs, social and economic justice, and populations at
risk (content for advanced competency #5 & #6).
III. UNITS AND CONTENTS – (Assigned readings are noted under the sessions in which they
will be covered.)
•
Unit 1 (Session 1): Ethics and Value Issues in Statistical Analyses
Introductions; Review of course syllabus and requirements; Addressing the regard for
individual worth, dignity, and self-determination in research, and identifying needs for and
responses to social work research.
•
Unit 2 (Session 2): Univariate Analysis
Review of key terms and concepts; Coding and data preparation; Introduction to SPSS;
Frequencies, mean, mode, median, variance, & standard deviation. In class exercises.
Readings: Weinbach & Grinnell, chapters 1 – 3
•
Unit 3 (Session 3): Normal Distribution
Measures of dispersion; Central Limit Theorem, probability, Z scores.
Readings: Weinbach & Grinnell, chapter 4
•
Unit 4 (Sessions 4 & 5): Probability/Sampling/Hypothesis Testing/Estimation
Theoretical sampling distributions, probability, and types of error. Developing and testing
hypotheses resulting in the ability to assess results of an evaluation and modify treatment
goals as needed (ADP practice behavior 10.8).
Readings: Weinbach & Grinnell, chapters 5 & 6
Units 5 though 8 cover specific statistical analysis methods students will need in order to
critically analyze, monitor, and evaluate their own practice interventions and the
effectiveness of social welfare programs (MCP practice behaviors 10.10 and 10.11).
•
Unit 5 (Sessions 6, 7, & 8) T-tests and F-tests (ANOVA)
One-tailed, two-tailed, equal and unequal variances, post hoc tests. In class exercises.
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Readings: Weinbach & Grinnell, chapter 11
•
Unit 6 (Sessions 9 & 10) Bivariate Categorical Procedures
Cross tabs and Chi square; Selecting an appropriate statistical test. In class exercises.
Readings: Weinbach & Grinnell, chapters 7 & 10
• Unit 7 (Sessions 11 & 12) Bivariate Correlation and Regression
Scattergrams, regression lines, Pearson's rho, standardized and unstandardized regression
(beta) coefficients. In class exercises.
Reading for Unit 7: Weinbach & Grinnell, chapters 8 & 9
• Unit 8 (Session 13). Introduction to Multiple Regression
Linear and hierarchical regression procedures. In class exercises.
Readings: Weinbach & Grinnell, chapter 9

Unit 9 (Session 14). Group presentations (20 pts).
Critiquing empirical research articles and utilizing evidence-based research to evaluate,
select, and use effective intervention strategies in working with individuals, families, groups,
and organizations (MCP practice behavior 3.1 and ADP practice behavior 6.1). Review for
final assessment.

Unit 10 (Session 15). Final assessment and article critique.
METHODS OF INSTRUCTION
The methods of instruction in this course include lecture, discussion among class members,
assigned readings, and working on statistical problems. It is unwise to miss classes in this course
due to the complexity of the subject. Examinations and assignments cover lecture and assigned
reading. Lectures often go beyond the assigned reading in presenting details. Also, student
notes are rarely useful to students who miss this class because of the type of material presented.
Required Textbook:
Weinbach, R.W., & Grinnell, R.M. (2010). Statistics for social workers (8th ed.). Boston, MA:
Pearson Education, Inc.
Highly Recommended Workbook:
Blanksky, P.E., & Barber, J.G. (2006). SPSS for social workers: An introductory workbook.
Boston, MA: Pearson Education, Inc. Contains disk of data to be used in class.
A copy of the student version of SPSS has also been shrink-wrapped with texts and is available
in the UALR bookstore.
Recommended Textbook:
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Lomand, T. C. (Ed.). (2007). Social science research: A cross section of journal articles for
discussion and evaluation, (5th Ed). Los Angeles, CA: Pyrczak Publishing.
METHODS OF EVALUATION
Your grade in this course is based on in class assignments, homework assignments, a group
assignment, a written critique of a professional article assigned in class, and class participation as
described below:
Five written homework assignments (20 points each; 40% of grade) on the following topics:
1) Univariate statistics (frequencies, mean, median and mode); 2) t-tests (comparison of means);
3) F-tests/ANOVA (comparison of two or more group means); 4) chi-square; and, 5) correlation
and simple regression.
In class and homework exercises (75 points; 30% of grade): Students are expected to attend
class on-time, to complete the assigned readings and exercises, and to be able to participate in
discussions about the course assignments and activities. Students will work in small groups and
individually to complete a variety of exercises on interpreting basic statistics. Students must be
present to receive credit for in-class assignments. Empirical journal articles will also
occasionally be assigned to be read for class discussion or homework assignments.
Group Presentation (25 points; 10% of grade): Students will work in groups of 3 or 4 to
present a critique of an article of the group’s choice. Specific guidelines for this assignment will
be provided in class.
Final Assessment and Article Critique (50 points; 20% of grade): Students will complete a
written assessment of knowledge of the materials covered in this course. The assessment will
consist of a combination of objective measures and a series of short essay questions. A copy of
the empirical research article to be critiqued will be provided in class the week before the
assessment.
Grading Scale
92 - 100
A
82 - 91
B
72 - 81
C
71 or below F
(230 to 250 points)
(205 to 229 points)
(180 to 204 points)
(179 points or lower)
Expectations for written work: Assignments should be carefully proofed for spelling and
grammar. Points will be deducted from assignments containing poor grammar and spelling. Text
citations and reference lists must be in correct APA (5th ed.) format. All sentences should be
carefully comprised of a student’s own words. Ideas, information, and concepts that originated
with any other source, as well as quotations (which should be used sparingly) must be correctly
cited in APA style. Material that is not correctly cited is considered to be plagiarized and
provides grounds for academic discipline.
Plagiarism is a grave violation of academic integrity. Students must know what constitutes
plagiarism, and must not commit it, either knowingly or unknowingly. Plagiarism may constitute
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grounds for failure on the assignment, failure in the course, and filing of an academic grievance
against the student.
NOTE: Failure to turn in any part of an assignment by the due date will result in an automatic
deduction of 2 points for each day late, unless prior approval is obtained from the instructor.
Assignments that are emailed (as attachments) will be counted as “received” at the time they
appear in the instructor’s Inbox; however, only hard copies of assignments will be graded.
Therefore, if an assignment is turned in via email, the student must also provide a hard copy to
the professor as soon as possible.
Class Attendance: Learning in a graduate professional program is based in large part on the
interaction that occurs between instructor and students in the classroom. Regular attendance in
class is an expected professional responsibility of the student. Absences of greater than 20
percent of the total number of classes can constitute grounds for failure in the course. This is a
school policy.
Students with disabilities: It is the policy and practice of the University of Arkansas at Little
Rock to create inclusive learning environments. If there are aspects of the instruction or design
of this course that result in barriers to your inclusion or to accurate assessment of achievement-such as time-limited exams, inaccessible web content, or the use of non-captioned videos--please
notify the instructor as soon as possible. Students are also welcome to contact the Disability
Resource Center, telephone 501-569-3143 (v/tty). For more information, visit the DRC website
at www.ualr.edu/disability.
Honor Code Statement: All students registered for all courses in the School of Social Work are expected
to adhere to the rights, responsibilities, and behavior as articulated in the UALR Student Handbook and the
NASW Code of Ethics. An essential feature of these codes is a commitment to maintaining intellectual
integrity and academic honesty. This commitment insures that a student of the School of Social work will
neither knowingly give nor receive any inappropriate assistance in academic work, thereby affirming
personal honor and integrity.
OTHER STATISTICS BOOKS
Elementary Statistics
Blalock, H. M. (1996). Social statistics (4th ed.). New York: McGraw Hill. (clear presentation of
elementary statistics).
Hays, W. L. (1998). Statistics (7th ed.). New York: Holt, Rinehart & Winston. (excellent
reference text — a classic)
Weinbach, R. W., & Grinnell, R. M. (2007). Statistics for social workers (7th ed.). White Plains,
NY: Longman Publishers.
Nonparametrics
Conover, W. J. (1971). Practical nonparametric statistics. New York: Wiley.
Regression and Other Multivariate Procedures
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Bollen, K. A. (1989). Structural equations with latent variables. New York: John Wiley and
Sons.
Cohen, J., & Cohen, P. (1983). Applied multiple regression/correlation analysis for the
behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum. (classic)
Fienberg, S. E. (1991). The analysis of cross-classified categorical data. Cambridge, Mass.: MIT
Press.
Freund, R. J., & Wilson, W. J. (1998). Regression analysis: Statistical modeling of a response
variable. New York: Academic Press.
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In Class & Homework Assignments
Homework 1 – Univariate Statistics (maximum grade 20 points).
Instructions: Using a data file from the SPSS for Social Workers or other data you may have
available (a secondary data set will be available in class), analyze the file using descriptive
statistics and report your findings. Choose 6 (at least 2 need to be continuous) variables from the
file and write a report describing the sample and their characteristics. For each variable, provide
the operational definition (.5), and then describe the univariate statistical findings (2pts),
using frequencies and/or measures of central tendency and dispersion where appropriate. For
example, state “The average age of the sample was ---, with a standard deviation of …” or
“There were __ males ( %) and __ females ( %).” A second section should discuss the
findings (5pts)--e.g., are these data different than you would have expected, in line with what
you have seen in the literature, etc.
Homework 2 – T-tests (maximum grade 20 points)
Instructions: Using the data set of your choice, analyze data using the t-test. Your grouping
variable should be a dichotomous variable (e.g., male, female) and your dependent or test
variables should be continuous (scales are best here—please look at raw data to be sure your data
are continuous!). Perform three t-tests. Present the results of the t-test analysis and then provide
your interpretation of the analyses and what they mean.
Homework 3 – ANOVA (F-tests) (maximum grade 20 points)
Instructions: Using the data set of your choice, run two ANOVA analyses. You will need a
continuous dependent (test variable) and a grouping (categorical) variable of 3 or more groups.
Present the results of the analyses and then provide your interpretation of these results in 2-3
pages.
Homework 4 – Chi-Square (maximum grade 20 points)
Instructions: Using the data set of your choice, run three Chi Square analyses. You will need to
make sure you are using categorical variables. Write up your findings and discuss them in two or
three type-written pages.
Homework 5 – Correlation and Simple Regression (maximum grade 20 points)
Instructions: From the data set of your choice identify at least 5 variables and correlate them with
one another. Interpret results and discuss your findings in 2-3 pages.
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In class and workbook exercises (75 points total; 30% of grade)
Throughout semester as assigned in class.
Students will work in small groups and individually to complete exercises on understanding and
interpreting statistical analysis. This will involve question sets based on empirical journal
articles, statistical tables from a variety of sources, and workbook exercises.
Group Presentations (maximum grade 25 points; 10% of final grade)
Instructions: Divide into groups and critique a research article. Divide the article into sections-introduction, methodology, results, and discussion--with a member of the group responsible for
the critique of each section. Use the instructions below for guidance on how to critique an
empirical research article. Prepare an informal presentation of the article critique for the class.
Critical Evaluation of Literature for Group Presentation and Final Assessment
The following areas of the research article should be addressed:
Introduction:
 Goals of the research (clearly stated?)
 Research question and hypotheses (clearly presented?)
 Review of the literature (current? pertinent to research question?)
 Statement of the problem
Methodology
 Type of study (appropriate? Survey/questionnaire/interview format?)
 Sample (how defined? Diversity?)
 Sampling method (probability or non-probability?)
 Measures (Are validity and reliability addressed?)
 Procedures (recruitment of sample; data collection)
Results
 Appropriate statistical methods?
 Interpretation of statistics?
 Are the results worthy of note? Statistical significance/clinical significance?
Discussion
 Are the results properly interpreted?
 Do the authors have appropriate statistical support for their conclusions?
 Fit with previous literature?
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