In-depth introductory statistical methods, focusing on inference,
alignment between study design and conclusions, and real-world
decision making. Includes parametric and non-parametric
approaches to one- and two-sample inference for means and
proportions, Type I and II errors, power; chi-squared tests and
simple regression. Course will be implemented in R.
Athena Title
Stat Methods Data Scientists
Semester Course Offered
Offered fall and spring
Grading System
A - F (Traditional)
Student Learning Outcomes
Students will identify and apply appropriate statistical methods to analyze data.
Students will use software to perform traditional statistical analyses as well as simulations to explore and analyze data.
Students will present and interpret statistical results in a clear and accurate manner, effectively communicating their implications to both technical and non-technical audiences.
Students will evaluate the alignment between study design and the conclusions drawn on real-world decision-making.
Topical Outline
types of study designs
inference for one and two sample means and proportions using parametric as well as nonparametric methods
