, or equivalent, instructor may review syllabi
of previously taken courses (past 5 years) and/or require a test to
assess the equivalence of the student background, as necessary.
HS 851 introduces students to applied inference methods in studies
involving multiple variables. Specific methods that will be discussed
include linear regression, analysis of variance, and different regression
models. This course will emphasize the scientific formulation, analytical
modeling, computational tools and applied statistical inference in diverse
health-sciences problems. Data interrogation, modeling approaches, rigorous
interpretation and inference will be emphasized throughout.
HS851 is a 4 credit hour course (3 lectures + 1 lab/discussion).
Students will learn how to:
- Understand the commonly used statistical methods of published scientific papers
- Conduct statistical calculations/analyses on available data
- Use software tools to analyze specific case-studies data
- Communicate advanced statistical concepts/techniques
- Determine, explain and interpret assumptions and limitations
- ρ and slope inference, 1-2 samples
- ROC Curve
- Non-parametric inference
- Cronbach's α
- Measurement Reliability/Validity
- Survival Analysis
- Decision theory
- CLT/LLNs – limiting results and misconceptions
- Association Tests
- Bayesian Inference
- PCA/ICA/Factor Analysis
- Point/Interval Estimation (CI) – MoM, MLE
- Instrument performance Evaluation
- Study/Research Critiques
- Common mistakes and misconceptions in using probability and statistics,
identifying potential assumption violations, and avoiding them
Teaching and Learning Methods
This is a 4-credit hour class that uses technology-enhanced and data-driven instructional
techniques. Synchronous web-streaming of lectures/labs and
asynchronous virtual office hour forums will be utilized. Assignments will be
announced on the course website and will be electronically collected, graded and recorded.
A variety of teaching methods will be used including lecture, Journal Club,
discussion, small group work, and guest presentation.
additional resources will be made available through the
and may include chapters,
websites for review, references, reports posted online, ebooks and other learning
Assignments and Evaluation Methods
- 40% Homework Projects
- 30% Midterm Exam
- 30% Final Paper
In this class, we will use the
official UMich online gradebook (restricted access) for grading
based on standard letter-grading distribution:
- A: 90%+
- B: 80-90%
- C: 70-80%
- D: 60-70%
- Plus and minus grads will also be used
(e.g., "B-": 80-83%; "B+": 87-90%)
The lowest graded Homework assignment will be dropped.
All Homework assignments must be completed by the corresponding
deadline, however. No late assignments will be accepted. For students
with genuine documented reasons for missing the midterm arrangements
will be made. If after receiving the graded exams or HW/projects back
you believe a grading error has occurred please see Dr. Dinov or your TA,
within one week. Late regrade requests may not be accommodated.
Reading assignments will be given. You will be responsible for the
information covered in these assignments. Lecture and discussion
attendance will be recorded from time to time.