Provides an exposure to advanced statistical methods, beyond
regression and analysis of variance, and introduces the
student to a data-analysis experience related to a real
scientific problem. In addition to learning and applying
statistical techniques, effective oral and written
communication of methods and results are emphasized.
Athena Title
Statistical Capstone Course I
Equivalent Courses
Not open to students with credit in STAT 5010
Non-Traditional Format
This version of the course will be taught as writing intensive,
which means that the course will include substantial and
ongoing writing assignments that a) relate clearly to course
learning; b) teach the communication values of a discipline—for
example, its practices of argument, evidence, credibility, and
format; and c) prepare students for further writing in their
academic work, in graduate school, and in professional life.
The written assignments will result in a significant and
diverse body of written work (the equivalent of 6000 words or
25 pages) and the instructor (and/or the teaching assistant
assigned to the course) will be closely involved in student
writing, providing opportunities for feedback and substantive
revision.
Prerequisite
STAT 4220 and STAT 4230/6230 and (STAT 4365/6365 or STAT 4365E/6365E)
Pre or Corequisite
STAT 4510/6510
Semester Course Offered
Offered fall
Grading System
A - F (Traditional)
Student learning Outcomes
Students will be able to understand advanced statistical methods which will round out their education.
Students will be able to understand advanced statistical methods which will help them see that there is more out there than t-tests, ANOVA, and regression.
Students will be able to understand advanced statistical methods which will give them more confidence in their own data analysis skills.
Students will be able to understand advanced statistical methods which will make them more attractive to prospective employers.
Students will understand how to write about statistical methods and results effectively.
Students will have completed several writing assignments during the Statistical Capstone courses sequence, culminating in a final report of their data analysis project.
Topical Outline
A wide variety of topics can be covered in this capstone course. Since all students will have gone through courses in which they learned the basic methods of regression and ANOVA, instructors can concentrate on other techniques according to their preferences, the preferences of the class, and the particular projects the students will be working on. Possibilities include time series analysis, data mining, factor analysis, classification and regression trees, smoothing, bootstrap, and categorical data analysis (contingency tables, loglinear models). The idea is not to go into any one of these topics in-depth and exclusively; rather, we propose covering many different topics over the course of the year, spending at most two or three lectures on each. In addition, the course will include units on effective communication (written and oral) and how to make a poster presentation. The rest of the class periods will be used for student presentations of their data sets and analyses.
