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Objectives and Structure of the CourseCSSS 321 is an introductory course in statistical
reasoning for social science students that emphasizes the use of cases
addressing substantive questions. The course will be driven by a practical, hands-on approach: The most effective way to learn statistics is by actively engaging in doing the statistical analysis. The material presented in the course will be analyzed using techniques that are typically taught in a traditional introductory course (see the syllabus for a description). The cases will be grouped by broad statistical topics, and arranged by topics in a sequence that is conventionally followed in a beginning course. There will be a certain progression in the material: concepts from data analysis will be used in subsequent cases dealing with applied probability, and statistical inference, and so forth. This course is part of a
three-quarter sequence. This course will cover the fundamental ideas of
statistical reasoning and the central role that measurement plays. It will
also introduce methods for exploratory data analysis, and the fundamentals of
probabilistic reasoning. This course may be preceded by CSSS 320 ‘Evaluation
of Evidence’, a course in quantitative thinking offered in the Autumn. The third component (CSSS 322,
Spring 2007) is a continuation, progressing to questions of assessing the
weight of evidence and more sophisticated models including regression-based
methods. Throughout both these courses the understanding of the underlying
concepts will be stressed. Details of the topics and cases for both courses
are provided in the syllabus. This sequence 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 three lectures,
a ‘laboratory’
session, and a ‘question session’ each week. The objective of the is to help students develop the skills necessary to analyze real data and hence learn the underlying statistical concepts. This laboratory serves a similar role as a chemistry or physics laboratory does; it provides an opportunity for you to interactively uncover the information in a data set in the context of answering questions about the situation that the data relates to. The idea is to train yourself in the process of analyzing real data, which is a skill that you will need here at UW and in your post-UW years. Each week, there
will be a three-part assignment to complete by the next week. The three parts
of the assignment are: 1. Readings from the
textbook Mind On Statistics and in CyberStats 2. Interactivities
to explore in CyberStats 3. Exercises to be
turned in, from Mind On Statistics and/or CyberStats The question session each week will focus on material from Exercises and Interactivities. Textbooks[M] Utts, Jessica, and Heckard, Robert. (2006). Mind on Statistics,3rd Ed. Thomson: Brooks/Cole. ISBN: 053499864X Required. [CHS] Chatterjee, Samprit, Handcock, Mark S., Simonoff, Jeffrey S. (1995). A Casebook for a First Course in Statistics and Data Analysis, Wiley: New York. Optional. Cyberstats and Intranet ResourcesThe course will make extensive
use of the web as a source of statistical information and for the course
materials. Much of the conduct of the class will take place via the
web. In particular we will use the
web-based courseware ThomsonNOW
including Cyberstats. It is a resource with many components (e.g., units,
exercises). We will use it to visualize the behavior of statistical concepts
through the use of conceptual software. To use thomsonNOW and
Cyberstats, you must signup
for it under ThomsonNOW. Where appropriate, reports and
homeworks will be submitted and reviewed over the UW intranet. Message board and Discussion Forum
I will be using the message board to provide discussion of issues in class and related questions. For questions that might be of interest to other students, please use the message board rather than solely emailing me. Example of questions are about interesting articles you have seen in the media, problems with access to resources, homework or computer questions. Enjoy! Please regularly consult this class home page and message board. It will contain lecture notes, homework, solutions and course information. Computer Usage and SoftwareThe computer is the scientific laboratory of the applied researcher in quantitative fields. As such this course requires the student to develop a degree of comfort and competence ‘in the lab’. Course Requirements and GradesThe grade for this class will
be based on a mid-quarter exam (30%), a final exam (35%), laboratory
work (10%) and homework assignments (25%). The assignments and
laboratory work will involve the analysis of real data sets using appropriate
computer software. The in-class examinations
consist of two 50 minute closed-book examinations. The exams are
non-cumulative. Students will be allowed to bring a single page of formulae
to the exam. Assignments and LaboratoriesNone of the assignments or the laboratory are optional. All homework will be due at the beginning of the class on the assigned due date. To allow for unexpected emergencies or extraordinary bad luck, the lowest homework score will be omitted from the grade computation. The purpose of the assignments
and laboratories is to develop facility in statistical thinking through
regular practice and to provide you with regular feedback on your performance
throughout the course. The assignments will be used mostly to determine
borderline cases, such as the difference between a B+ and an A-. However I
regard the assignments as essential to the course: failure to do the
assignments will result in a significant penalty to your grade! Don't hand in assignments late! This is the reason most students who get in trouble do so! It will affect your grade Assignments that are up to one week late will be penalized points; assignments from one to two weeks late will be penalized 3 points; assignments from two to three weeks late will be penalized 6 points; assignments more than three weeks late will not be accepted. 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 ‘iin committee’i 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.’) Question SessionsThe teaching assistant (Krisztian Sebestyen) will be available to discuss questions you may have about the homework. They will also conduct the ‘question session‘ to discuss questions that arise in classes and exercises. This course is time consuming. If you do ‘A’ work you will receive an ‘A’ grade. The grade of incomplete will be given only in clear cases of emergency. 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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