Objectives of the Course
The computer is the scientific laboratory of the applied researcher in the social sciences. It plays the same role for the empirical social science research as the traditional laboratories play for physics and chemistry researchers. As such this course should allow the student to develop a degree of comfort and competence “in the lab.”
The primary purpose of this course is to provide students with a common set of core knowledge about computing resources available to them for their class work and doctorial research. This knowledge has two components. The first are primary elements of computing that are necessary to understand so as to make use of the available resources (e.g., interfaces, networking, storage, input/output, numerical computation). The second are the constantly evolving particular resources available to them at UW (e.g., laboratories, data bases and software packages).
The intent is not to provide in-depth courses in the use of these packages, but to introduce students to the purposes and nature of such packages. It is expected that students will turn to short courses given by the C&C, CSSCR and MSCC for information about the detailed use of some the these resources and all packages.
Overall, this course should enhance the learning of students in their quantitative courses by providing them with knowledge of the core computing resources that can be bought to bear on the questions posed in the courses. It will also speed the integration of students into research teams and better prepare them for their subsequent research careers.
This course is part of the curriculum of the new Center for Statistics and the Social Sciences (CSSS), with funding from the University Initiatives Fund. The CSSS is includes faculty members from the Department of Statistics and a broad-range of social science disciplines including Anthropology, Economics, Geography, Political Science, and Sociology. This curriculum is been developed to complement and strengthen the quantitative methods course offerings for social science students at both the undergraduate and graduate levels.
Structure of the Course
There will be a once per week integrated lecture covering various aspects of computer usage in the social sciences.
The first lectures will be on “resources on resources”: the availability of resources to find and explore computing resources. Examples of these are information on the UW web page, web interfaces to libraries, key data and information sources on the non-UW web and network connections to computing resources. It is presumed that the students will be familiar with the basics of PC-based computing.
The next lectures will overview UNIX-based computing (i.e. introduction to the UNIX command-line interface and resources). Subsequent lectures will focus on four major statistical packages, SAS, SPSS, SPLUS and STATA. Comparisons of the capabilities of these packages and other computing software will be developed.
Approximately half the lectures will be held in a computer laboratory so that students can learn “hands on” about the resources.
[VR] Venables, William N., and Ripley, Brian D. Modern Applied Statistics with S, 4rd Ed. (2002) Springer-Verlag: New York. ISBN 0-387-95457-0 Not Required.
Course Requirements and Grades
There will be weekly homeworks and exercises relating to computing and programming. Students will be graded on a scale of 1 to 10 for each homework. As each of the exercises relates to a different aspect of the computing environment (e.g., Basics of UNIX user interface, fundamentals of Splus and SAS programming), students must achieve an acceptable grade on each homework to pass the course.
Discussion of homework problems is encouraged. However, each student is required to prepare and submit solutions (including computer work) to the assignments and project on their own; solutions prepared “in committee” are not acceptable. Duplication of homework solutions and computer output prepared in whole or in part by someone else is not acceptable and is considered plagiarism. If you receive assistance from anyone, you must give due credit in your report. (Example: “Since the data are all positive, and skewed to the right, a logarithmic transformation is clearly appropriate as a next step. I thank David Cox for pointing this out to me.”)
I welcome comments or suggestions about the course at any time, either in person, by letter, or by anonymous email. Please feel free to use these ways make comments to me about any aspect of the course.
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STUDENTS WITH DISABILITIES
If you have a disability that requires special testing accommodations or other classroom modifications you need to notify the instructor and the Office of Disabled Student Services as soon as possible. You may contact the DSS office at 543-8925.