Course ID: | STAT 4210. 3 hours. |
Course Title: | Statistical Methods |
Course Description: | A survey of statistical methods that introduces experimental
design and analysis of variance; multiple linear regression;
analysis of categorical data, including chi-squared tests of
independence and goodness-of-fit; non-parametric tests, including
tests based on resampling; and statistical power. Emphasizes
precise statistical communication and implementation using
statistical software. |
Oasis Title: | Statistical Methods |
Duplicate Credit: | Not open to students with credit in STAT 4110H |
Prerequisite: | STAT 2000 or STAT 2000E or MSIT 3000 or MSIT 3000H or MSIT 3000E or BUSN 3000 or BUSN 3000E or BUSN 3000H |
Semester Course Offered: | Offered fall, spring and summer semester every year. |
Grading System: | A-F (Traditional) |
|
Course Objectives: | The goal of this course is to reinforce conceptual
understanding of study design, descriptive statistics, and
inference and to extend those concepts to more advanced
statistical methods. These methods include analysis of
variance; multiple linear regression and residual diagnostics;
analysis of categorical data, including chi-squared tests of
independence and goodness-of-fit; and non-parametric tests,
including tests based on resampling. For each statistical
method introduced, students will calculate summary statistics
and create appropriate data visualizations using statistical
software. Coverage of inference will include hypothesis tests,
confidence intervals, effect sizes, and a discussion of the
strength and limitations of each. Students will gain a better
understanding of Type I and II errors and the statistical
power of a hypothesis test. The course will emphasize precise
statistical communication throughout, with careful attention
to the alignment between study design and conclusions drawn. |
Topical Outline: | A survey of statistical methods that introduces experimental
design and analysis of variance; multiple linear regression;
analysis of categorical data, including chi-squared tests of
independence and goodness-of-fit; non-parametric tests,
including tests based on resampling; and statistical power. The
course emphasizes precise statistical communication and
implementation using statistical software. |