From: web-form@Oswego.EDU
Sent: Tuesday, December 04, 2007 10:22 AM
To: ucc@oswego.edu
Subject: Web Form: Course_Submission

Department_Chair: Margaret Ryniker
Department_Chair_Email: ryniker@oswego.edu
Additional_Contact: Ernest Nickels
Additional_Contact_Email: nickels@oswego.edu

Course_Number: PBJ 387
Course_Type: New Course
Course_Title: Research Methods and Data Analysis

Catalog_Description: This course provides an introduction to the philosophy and methods of social scientific research and to the elementary techniques of data analysis, paying particular attention to how empirical inquiry can be used to advance understanding and social policy pertaining to crime, deviance, and public justice. 

Prerequisites: minimum 27 credits or permission of instructor 
Sp_every Spring: Yes
Semester_Hours: 3

Justification: The Public Justice department has wished to add such a course to its offerings for some time, and now finds itself in a position to do so after recent additions to its faculty. The department's most recent program review identified this area as the missing piece in its curriculum. Recent trends in justice studies programs have favored the incorporation of methodological and statistical training at the undergraduate level. Adding this offering helps ensure our program stays in line with the changing educational standards for the discipline (e.g., as articulated by the Academy of Criminal Justice Sciences) and that our students are competitive in the job market and in placements to graduate programs in this field.  

Course_Objectives: By introducing methods and statistics together in the same course, students have an opportunity to see the research process through from start to finish. Over the course of the semester, students will be asked to design a study, collect data, analyze it and report their findings in the form of a scholarly article which they will then present for review by their peers in the class prior to submission of their final revision. The nature of this project, the major assignment of the course, is writing intensive. 

Course_Description: Research methods will be the focus of the first half of the semester, beginning with a foreword on the nature of scientific knowledge and the logic of discovery. Major topics in this portion of the course will include research ethics and design; the purpose and procedures of sampling; conceptualization and measurement; and the conduct of statistical surveys, participant observations, and evaluation research. The latter half of the semester, then, will be devoted to the basics of quantitative analysis—to the use of descriptive and inferential statistics. Descriptive statistics refer to the use of numbers to summarize the essential characteristics of a set of data. This includes measures of central tendency (e.g., the arithmetic mean) and measures of dispersion (e.g., the distance between data points from the mean). Inferential statistics then use these basic descriptive devices to summarize data that has been drawn from a sample, plus a few principles of probabilty to create inferences 
about whole populations and to test hypotheses. Specifically, this course will look at estimation techniques (i.e., confidence intervals); tests of significance for contingencies in categorical data (i.e., chi-square) and those involving proportions and means in one or more populations (i.e., one sample, independent and paired samples z- and t-tests; univariate analysis of variance); bivariate correlation (i.e., Pearson); and simple linear regressions (i.e., univariate Ordinary Least Squares). Time permitting, more sophisticated variants of these tests—multivariate techniques—will also be introduced. Due in part to the accelerated nature of the course, this introduction to statistical techniques will de-emphasize the mathematical dimensions of quantitative analysis in favor of focusing instead upon the conceptual logic of these tests, the practical use of packaged software (e.g., SPSS), and the meaningful interpretation of the results of computer analyses.

Resources: Elementary social research methods and statistics are heavily standardized subjects. If students find they require reading materials beyond the assigned course texts (which is not anticipated), the current library holdings should be more than sufficient. Arrangements are being made for the necessary access to computer labs with the required software.

Bibliography: 
Assigned Texts: 
Maxfield, M. G., & Babbie, E. R. (2005). Basics of research methods for criminal justice and criminology. Belmont, CA: Wadsworth. 
Bachman, R., & Paternoster, R. (2003). Statistics for criminology and criminal justice (2nd ed.). New York: McGraw-Hill.

Supporting Texts:
Abelson, R. (1995). Statistics as principled argument. Hillsdale, NJ: Lawrence Erlbaum Associates. 
Berg, B.L. (1995). Qualitative research methods for the social sciences (2nd ed.). Boston: Allyn and Bacon.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, N.J.: Erlbaum.
Bohrnstedt, G.W., & Knoke, D. (1988). Statistics for social data analysis (2nd ed.). Itasca, IL: F.E. Peacock Publishers.
Brown, S.R., & Melamed, L.E. (1990). Experimental design and analysis. Newbury Park, CA: Sage.
Coffey, A., & Atkinson, P. (1996). Making sense of qualitative data. Thousand Oaks, CA: Sage.
DeVaus, D.A. (1995). Surveys in social research (4th ed.). St. Leonards, NSW: Allen & Unwin.
Gentleman, J.F., & Whitmore, G.A. (Eds.). (1994). Case studies in data analysis. New York: Springer-Verlag.
Girden, E.R. (1996). Evaluating research articles from start to finish. Thousand Oaks, CA: Sage.
Grimm, L.G., & Yarnold, P.R. (Eds.). (1995). Reading and understanding multivariate statistics. Washington, DC: American Psychological Association.
Jorgensen, D.L. (1989). Participant observation: a methodology for human studies. Beverly Hills, CA: Sage.
Kuhn, T. (1996). The structure of scientific revolutions (3rd ed.). Chicago, IL: University of Chicago Press. 
Kvale, S. (1996). Interviews: an introduction to qualitative research interviewing. Thousand Oaks, CA: Sage.
Lee, R.M. (1995). Dangerous fieldwork. Thousand Oaks, CA: Sage.
Mangione, T.W. (1995). Mail surveys: improving the quality. Thousand Oaks, CA: Sage.
Nachmias, C., & Nachmias, D. (1992). Research methods in the social sciences (4th ed.). New York: St. Martin's Press.
Pilcher, D.M. (1990). Data analysis for the helping professions: a practical guide. Newbury Park, CA: Sage.
Popper, K. (1959). The logic of scientific discovery. New York: Basic Books. 
Reid, W.J., & Smith, A.D. (1989). Research in social work (2nd ed.). New York: Columbia University Press.
Royse, D.D. (1991). Research methods in social work. Chicago: Nelson-Hall Publishers.
Siegel, S., & Castellan, Jr., N.J. (1988). Nonparametric statistics for the behavioral sciences (2nd ed.). New York: McGraw-Hill.
Sutton, C. (1987). A Handbook of research for the helping professions. New York: Routledge & Kegan Paul.
Tripodi, T., & Epstein, I. (1980). Research techniques for clinical social workers. New York: Columbia University Press.
Weinbach, R.W., & Grinnell, R.M. (1995). Statistics for social workers (3rd ed.). White Plains, NY: Longman.
Williams, M., & May, T. (1996). Introduction to the philosophy of social research. London: University College London Press.

Other_Comments: 
IP_Adress: 129.3.51.11