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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 CourseThere
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. Textbooks[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 GradesThere 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. Use the menu on the top-left of this page to find out more about the course. 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. |
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