LMP2004H: Introduction to Biostatistics
Who can attend
A maximum of 20 students can be enrolled in this course.
Ten of these will be from the MHSc in Laboratory Medicine program, while for the remaining 10 spots priority will be given to students from the research streams at the Department of LMP.
Course description
This course will introduce you to a wide variety of statistical concepts and methods that are commonly used in biological research.
You will learn how to review different types of data, structure questions of that data using appropriate statistical approaches, and review the use of statistics in scientific literature.
You will be introduced to limitations and assumptions that underly statistical analyses.
By the end of the course, you should be familiar enough with statistics to be avoid most of the following errors in your analysis (or at least know when you need to look up how to avoid them) or spot them in studies you may read:
- Failures to clearly state hypotheses being tested
- Failures to check the accuracy of data being used for analysis
- Failures to describe the statistical tests being used, or to properly describe the software/algorithms used to perform statistical testing
- Failures to understand the appropriateness of a statistical test for the problem at hand
- Failure to use control groups properly
- Misuse of one-tailed/two-tailed tests
- Misuse of paired/unpaired tests
- Failure to assess sample sizes and power calculations for the given experiments
- Confusing standard deviation and standard errors
- Use of multiple tests without using multiple testing corrections
- Misinterpretation of P-values, and mistaking statistical significance for importance
- Misleading use of data visualization
- Incorrect interpretations of sensitivity and specificity
Structure
You will be taught in twelve three-hour sessions:
- 1.5 hours: lecture
- 1.5 hours: hands on tutorial, discussing practical examples using the R software.
Course coordinator
Dr. Alla Slynko
lmp.grad@utoronto.ca for administrative queries.
Timings and location
Wednesdays 9:30 am – 12 pm
Location: TBA
Evaluation methods
Participation – 10%
Weekly assignments - 50% (5% each. Best 10 out of 11 for Weeks 2 - 12)
Mid-term exam - 20%: A mid-term examination will cover material up the lecture prior to the exam date.
Final examination - 20%
Late assignment policy
A 10% reduction of the grade will be applied for every day of late submission.
Missed exam policy
If you miss an examination and would like to write a make-up exam, you must submit a letter stating the reason for the request and provide support for it such as a note from a physician or other relevant documentation.
You must submit this within one week of missing the exam. Failure to do so will result in a zero mark for the evaluation.
Software
Access to and familiarity with a Windows computing environment is required for this course. Tutorials will present topics in the RStudio Desktop environment, with possible manipulation of data tables in Excel.
RStudio Desktop is available as an open source package and downloadable from the RStudio website.
Schedule
Lecture - date TBC |
Topic |
---|---|
Lecture 1 |
Introduction to course Basic statistical concepts Basic descriptive statistics Tutorial: Intro to RStudio |
Lecture 2 |
Types of data, continuous and discrete distributions More on descriptive statistics Outliers |
Lecture 3 |
Probability |
Lecture 4 |
Hypothesis Testing Type I/II Errors Parametric, Nonparametric tests (KS), Concordance, Power, sample sizing, effect sizes Multiple testing corrections |
Lecture 5 |
Analysis of variance |
Lecture 6 |
Correlations |
Lecture 7 |
Midterm Regressions I No Tutorial Today |
Lecture 8 |
Regressions II |
Lecture 9 |
Odds Ratio, Relative Risk, Attributable Risk, Number Needed to Treat Sensitivity/Specificity/ROC curves PPV/NPV |
Lecture 10 |
Serial Measurements, Time Series |
Lecture 11 |
Dose Response curves Survival Analysis |
Lecture 12 |
Resampling statistics Permutations, Monte Carlo methods |
Lecture 13 |
Final exam |
Text and readings
The main material for the course will consist of the slides presented in lectures, and these are based on material found in the online textbook: Hoffman et al. Basic biostatistics for medical and biomedical practitioners. 2019