utexas.eduSW388R7 Syllabus - Spring, 2000The University of Texas at Austin, School of Social Work Data Analysis and Computers II Description Objectives Teaching Methods Texts and Materials Requirements Schedule Assistance Course Number: SW 388R7 Faculty: Jim Schwab Unique Number: 60625 Office Number: SSW 3.106B Semester: Spring 2001 Office Phone: 471-9816 Time: Wednesday: 11:30 am to 2:30 pm Email: [email protected] Place: SSW 1.214 Office Hours: By appointment Web Page for Course: http://webct.cc.utexas.edu:8900/public/SW388R7_s00/ I. Course Description This course is designed to build upon the concepts and procedures introduced in Data Analysis and Computers I, to enable students to do a more thorough job of data analysis by introducing multivariate statistical procedures into their repertoire of statistical techniques. The primary focus is on using the SPSS statistical package for calculating multivariate statistics and the utilization of the statistical output in research findings. II. Course Objectives 1. To understand how the analysis of data derives from the statement of a research problem or hypothesis and the availability of empirical data . 2. To understand how to conduct a variety of statistical analyses, including testing of statistical assumptions, data transformations, and validation of statistical findings. 3. To understand how to present and interpret the results of statistical analyses. To be able to design a data analysis strategy that answers a research question or hypothesis, including specifications for data4. elements, requirements of the statistic, and limitations to the interpretation. III. Teaching Methods The analysis of data occurs in the context of specific research questions and hypotheses derived from existing research and practice knowledge bases. To provide this context to our learning, we will replicate the data analyses for a variety of research articles published in behavioral science journals, as well as sample problems from a variety of textbooks. The research articles that we will use have all utilized data from sources such as the General Social Survey (GSS) conducted by the National Opinion Research Center and available to us through the Internet. We will rely upon articles that provide us with enough detail to replicate the author's data set to a reasonable degree so that we may conduct statistical analyses parallel to those conducted by the researcher. In addition to providing a context for our analysis, this strategy will provide us with a wealth of pragmatic examples of how researchers conduct, present, and interpret their statistical analyses. A typical class presentation will begin with a review of text materials related to the statistical techniques we will employ in that class. We will conduct the analyses on the data problems presented in the textual materials. Next we will review the problem statement, literature review, and plan of data analysis from a published article that utilizes this statistical technique. We will download the raw data files used in this analysis, along with SPSS program files that transform the data into the format required by the statistical technique. We will first do exploratory data analysis on the data to examine its compliance with statistical assumptions. Next, we will do the statistical tests used in the research article and interpret our results in comparison to those of the article’s author. Finally, we will gently critique the analytic strategy of the researcher and propose, and possibly conduct,supplemental analyses that support further insights into the research issues or provide us with a context for evaluating the researchers findings. It is expected that students review the textual materials and replicate the data analyses several additional times before the next class until they have attained basic mastery of the analytic techniques and interpretations presented in the journal article, or identified topic areas that require further clarification. The data analysis and the supporting materials from the text will comprise the materials for a brief quiz at the start of the following class. IV. Required and Recommended Texts and Materials The required text for the course is: ● Hair, Joseph F., Jr; Anderson, Rolph E.; Tatham, Ronald L.; and Black, William C. Multivariate Data Analysis, Fifth Edition. Englewood Cliffs, New Jersey: Prentice Hall. In addition, you will need access to SPSS Version 10.0 on a PC computer and access to the Internet using either Internet Explorer or Netscape browser. If you do not have a personal computer, the necessary hardware and software are available in the LRC computer lab. The exercises for analyzing data are were developed using the WebCT course tools. Complete directions for conducting the data analyses are found in the WebCT class materials web pages. The research articles whose data analyses we will replicate will be placed on reserve in the LRC. All data sets used in this course will be available as SPSS system data files (".SAV") for downloading via the Internet. A link or reference to these files will appear on each class outline sheet for which the materials are prepared. V. Course Requirements Learning to analyze data requires experience as well as mastery of textual materials. This course has been designed to maximize the amount of time you spend doing data analysis. To provide you with indicators of your progress, we will have brief weekly quizzes that focus on the analysis conducted in the previous class and repeated in your homework preparation, as well as the supporting text materials for that analysis. Though the format of the quizzes will be pencil and paper, the quizzes will contain questions that require interactive SPSS analyses on the computer during the quiz. The quizzes for the last three years can be downloaded from my web site. This year's are most likely to resemble the quizzes of last spring and summer. There will be 12 weekly quizzes. The ten highest quiz grades will be used to compute the quiz grade. Makeup quizzes will not be given for any reason. If a student misses more than two quizzes during the semester, they will receive a grade of zero for that quiz. The midterm and final examination will be in the format of questions anticipated to be on future qualifying exams. In addition to outlining the analysis to solve a research problem, it is expected that future qualifying exams will include