EXMD 634
EXMD 634: Introduction to quantitative research methods for Experimental Medicine
Day & Time: 8:4511:45am Wednesdays (September 2 – December 2, 2020)
Place: EM1.3509, MUHC Glen site Online via Zoom
Instructor: Nandini Dendukuri
Email Address: nandini.dendukuri@mcgill.ca
Telephone: (514) 934 1934 x36916
Address: Centre for Outcomes Research, 5252 de Maisonneuve Ouest, 3F.50 Montreal, PQ H4A 3S5
Course description:
This course will familiarize graduate students in Experimental Medicine and other disciplines within the Faculty of Medicine with basic concepts of applied statistics. Motivating examples will be drawn from both clinical research and basic science research. These methods are necessary for the student to carry out their own research as well as to interpret research publications. This course will also serve as a foundation for more advanced courses in statistical modeling. The R statistical software package will be used for computation.
Assessment:
Homework: There will be six homework assignments during the course. Assignments must be handed in at the beginning of the class on the due date. These homework problems will count for 75% of the course mark.
Inclass miniquizzes: 10%
Project: Student are required to work in groups of 3, identify a dataset, preferably related to their graduate research, analyze it and prepare a report. The project will account for 15% of the course mark.
Suggested Reference:
 Statistics for the life sciences, Myra Samuels, Jeffrey Wittmer and Andrew Schaffner, 5^{th} edition, Pearson 2016 (student ebook available)
DATE  TOPIC  ASSIGNMENT 

September 2 (Lecture 1) 
• Introduction to the course • Sample size, precision, bias • Random sampling and randomization • Reporting guidelines 

• Introduction to R  
September 9 (Lecture 2) 
• Types of variables • Types of observational units • Types of study design • Laws of probability 

• Normal distribution • Binomial distribution • Random sampling and randomization • Poisson or negative binomial distribution 

September 16 (Lecture 3) 
• Central limit theorem  Assignment 1 due 
• Confidence intervals for a single mean  
September 23 (Lecture 4) 
• Confidence intervals for comparison of means • Sample size calculation based on confidence intervals 

• Hypothesis testing for a single mean and for comparison of means • Hypothesis testing vs Confidence intervals 

September 30 (Lecture 5) 
• Example problems involving ttests for one or two sample means  Assignment 2 due 
• Sample size calculation based on hypothesis tests (Type I vs. Type II errors) 

October 7 (Lecture 6) 
• Bayesian inference for one or two means  
• Probability of a wrong decision with hypothesis testing  
October 14 (Lecture 7) 
• Inference for a single proportion or comparison of two proportions: Confidence interval estimation • Sample size calculations based on confidence intervals • Inference for a single proportion or comparison of two proportions: Hypothesis testing 
Assignment 3 due 
• Sample size calculations based on hypothesis tests  
October 21 (Lecture 8) 
• Hypothesis tests for contingency tables (Chisquared test, Fisher’s exact test)  
October 28 (Lecture 9) 
• Nonparametric tests (sign test, Wilcoxon signed rank test, Wilcoxon rank sum test) Bootstrap Confidence Intervals 
Assignment 4 due 
November 4 (Lecture 10) 
• Oneway ANOVA • Null hypothesis and Ftest • Between and withingroups variance • Testing multiple comparisons 

November 11 (Lecture 11) 
• Twoway ANOVA • Randomized block design (or Repeated measures ANOVA) • Correlation 
Assignment 5 due 
November 18 (Lecture 12) 
• Simple linear regression: Model assumptions and estimation • Multiple Linear regression with two predictors 

November 25  Presentation of Course Project and submission of final course report  
December 2  Assignment 6 due 
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