SW 222 introduces the philosophies and value base of social welfare policy within the United States and examines the cultural traditions and political and economic forces that have contributed to the emergence of present social welfare policies and systems. Specific attention is paid to those most vulnerable due to age, ability, race, ethnicity, gender, socio-economic status, sexual orientation and the subsequent policies designed to address those specific needs.

This course provides an examination of the breadth and depth of the profession of social work as well as the philosophical perspectives and the professional value base. Public and private service delivery systems of social welfare and social needs (e.g., mental health services, education, child welfare) and various at-risk populations (e.g., due to statuses such as age, sexuality, religion, poverty, ability, etc.) are addressed. Theoretical foundations are identified as well as the problem solving framework of the social work profession.

This course provides an examination of the breadth and depth of the profession of social work as well as the philosophical perspectives and the professional value base. Public and private service delivery systems of social welfare and social needs (e.g., mental health services, education, child welfare) and various at-risk populations (e.g., due to statuses such as age, sexuality, religion, poverty, ability, etc.) are addressed. Theoretical foundations are identified as well as the problem solving framework of the social work profession.

May be repeated indefinitely.

May be repeated to a maximum of 12 hours.

Residency credit for dissertation research after the qualifying examination. Students may register for this course in the semester of the qualifying examination. A minimum of two semesters are required as well as continuous enrollment (Fall and Spring) until the dissertation is completed and defended.

Basic principles of statistical consulting including how to manage a consulting session, how to formulate and solve problems and how to express results both orally and in writing. Students will be expected to analyze data from a current consulting project. Lecture, two hours; laboratory, two hours per week.

Introduction to methods of analyzing data from experiments and surveys; the role of statistics in research, statistical concepts and models; probability and distribution functions; estimation; hypothesis testing; regression and correlation; analysis of single and multiple classification models; analysis of categorical data.

Multivariate normal distribution, linear models in matrix notation, multiple linear regression (distribution results, categorical predictors, interactions, connection to ANOVA, sums of squares, diagnostics, ridge and nonparametric regression), Generalized linear models (binomial, poisson, and gamma regression), overdispersion, mixed models, diagnostics, professional presentation of results.

Convergence concepts (Central Limit Theorem), Sampling from a Normal Distribution, Order Statistics, Methods for finding point and interval estimates, methods for finding hypothesis tests, sufficiency principle, methods for evaluating point estimators (mean square error, unbiasedness, Carmer-Rao lower bound), Asymptotic of point estimates, interval estimates, and hypothesis testing procedures.