Course Description
Provides students with 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 II
Equivalent Courses
Not open to students with credit in STAT 5020S, STAT 5020W
Prerequisite
(STAT 5010 or STAT 5010W) and (MATH 3000 or MATH 3300)
Semester Course Offered
Offered spring
Grading System
A - F (Traditional)
Student learning Outcomes
- Students will use advanced statistical methods that they have not encountered previously in their major coursework.
- Students will adapt statistical methods when underlying assumptions of traditional methods (such as t-tests, ANOVA, and regression) are not met.
- Students will recognize and employ ethical standards in statistical practice.
- Students will collaborate with a client in order to answer the client’s questions using the client’s data.
- Students will work effectively in a group setting toward the common goal of answering the client’s questions.
- Students will communicate with the client to explain the statistical tools and results in a way that the client can understand.
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.
Institutional Competencies Learning Outcomes
Analytical Thinking
The ability to reason, interpret, analyze, and solve problems from a wide array of authentic contexts.
Communication
The ability to effectively develop, express, and exchange ideas in written, oral, interpersonal, or visual form.
