Biostatistics

Queen's University
Search Type

Collaborative Program in

Biostatistics

site header

Courses Description


The following is a brief overview of course content of the Master of Biostatistics program, including 6 core courses offered by the Department of Public Health Sciences and Department of Mathematics and Statistics and some elective courses offered by the various departments identified.

Core courses

EPID 801: Introduction to Epidemiology

This course deals with the design and analysis of research in epidemiology. Topics include: measures of health status; risk factors and associations between them; study design including descriptive, analytical, experimental, and theoretical approaches; validity issues; critical appraisal; sources of data; and data collection and management.

Three term hours, fall, every year.


EPID 804: Intermediate Epidemiology

This course deals with advanced methods and issues in the design, conduct, analysis and interpretation of epidemiologic studies. The content focuses on observational study design and analysis, and builds on epidemiologic principles presented in EPID 801. Data analysis will emphasize te application and interpretation of statistical concepts in epidemiologic research.

Three term hours, winter, every year.


EPID 823: Advanced Methods of Biostatistics

An advanced course in the theoretical issues and analytical practices in epidemiology, and biostatistics. Major topics include the life-table method, demography and confounding and its solutions. Detailed design and analysis of cohort, case-referent and experimental studies shall be performed. Multi factor techniques including log-linear logistics and Cox's proportional hazards models will be discussed detail.

Three term hours, fall, every year.
Prerequisites: EPID 822 or equivalent ("equivalent" option applicable to MSc Collaborative Biostatistics students only


MATH 896: Core Course In Math Statistics (Core for Math and Stats only)

This course provides basic knowledge in mathematical statistics at the graduate level. Topics will include: Classical and Bayesian inference, Multivariate Gaussian distribution and its applications in Statistics; decision theory; basic techniques of non-parametric estimation.

Three term-hours, winter; lectures.


STAT 853: Statistical Inference (Core for Epidemiology only)

Decision theory and Bayesian inference; principles of optimal statistical procedures; maximum likelihood principle; large sample theory for maximum likelihood estimates; principles of hypotheses testing and the Neyman-Pearson theory; generalized likelihood ratio tests; the chi-square, t, F and other distributions.

Three term hours, winter, every year.
Offered jointly with STAT 463


STAT 862: Computational Data Analysis

An introduction to aspects of computer software consistent with modern professional practice of statistics. Particular attention is given to the use of the statistical packages R and SAS.

Three term hours, fall, every year.
Offered jointly with STAT 462


STAT 886: Survival Analysis

Introduces the theory and application of survival analysis: survival distributions and their applications, parametric and nonparametric methods, counting process and proportional hazards regression, planning and designing clinical trials.

Three terms hours, winter, every year.
Offered jointly with STAT 486


Department of Public Health Science Electives

EPID 812: Health Services and Program Evaluation

This course provides an introduction to public health program evaluation methods. The intent is to familiarize the student with the major issues, methods and challenges faced by program evaluators working in the field of public health. The emphasis will be on conceptual approaches, potential program design issues, and the interpretation and application of program evaluation findings.

Three term hours, winter, every year.


EPID 817: Foundations of Cancer Control (PDF, 153KB)

This course is intended for graduate students, clinical fellows and postdoctoral fellows who are engaged or interested in cancer research. This course will provide students with training in the fundamentals of epidemiologic methods in cancer research and with knowledge of how epidemiology could contribute to better understanding of cancer etiology and control in human populations. The course will focus on concepts and methodological issues central to the conduct of epidemiologic studies of cancer etiology and control. Topics will include: an introduction to basic epidemiologic concepts, biologic concepts central to the investigation of cancer, study design, clinical epidemiology, and cancer control and prevention.

Three term hours, winter, every year.


EPID 828: Infectious Disease

This course provides an introduction to the principles of infectious disease prevention and control relevant to public health practice. The course focuses on the etiology, history, societal impacts and determinants of infectious diseases. There is an emphasis on modern prevention and control efforts that can be applied at the local, national and international levels.

Three term hours, winter, every year.
Prerequisites: EPID 801 and EPID 821

Department of Mathematics and Statistics Electives

Elective courses 


STAT 855: Stochastic Processes and Applications

Markov chains, birth and death processes, random walk problems, elementary renewal theory, Markov processes, Brownian motion and Poisson processes, queuing theory, branching processes.

Three term hours, fall and winter, every year.
Offered jointly with MTHE/STAT 455)


STAT 864: Discrete Time Series Analysis

Autocorrelation and autocovariance, stationarity; ARIMA models; model identification and forecasting; spectral analysis. Applications to biological, physical and economic data.

Three term hours, fall, every year.
Offered jointly with STAT 464


STAT 871: Design and Analysis of Experiments

Analysis of variance for fixed, random and mixed models; analysis of covariance; distribution of mean squares; classical designs including fractional factorial experiments, Latin squares and split pilot designs. Model topics including Taguchi methods and designs for nonlinear models.

Three term hours, fall or winter, every year.
Offered jointly with STAT 471


MATH 895: Probability Theory

The course provides basic knowledge in probability at the graduate level. Topics will include: basic notions and concepts of Probability Theory; characteristics functions; law of large numbers and central limit theorem; martingales; stochastic processes.

Three term hours, fall, every year.


Interdepartmental Electives

Department of Psychology


PSYC 801: Design and Experiments

Topics include: The logic of the test for significance and controversies concerning it; ANOVA and its underlying linear model for between- subject, within-subject and split-plot designs; orthogonal comparisons for trend analysis and for special contrasts; restricted randomization and the randomized-block design; partial confounding in latin-squares; balancing conditions against trend; hierarchical designs; ANOVA and multiple correlation; designs including organismic variables; random- effect models and the fixed-effect fallacy; data transformations and non-parametric tests.

Three term hours, fall, every year.


PSYC 802: Introduction to Multivariate Analysis

Topics include: History of Multivariate Techniques, Matrix Algebra, Data Assumptions and Preparation, Multiple Regression, Canonical Correlation, Multivariate Analysis of Variance, and Discriminant Function Analysis.

Three term hours, fall, every year.


Department of Biology


BIOL 861: Introduction to Linear Models for Biological Data

This course is designed for Biology graduate students with a basic introductory statistics/experimental design course and a working knowledge of R, a Language and Environment for Statistical Computing. In-depth exploration of all aspects of fitting linear models to continuous and categorical data, using mainly the lm function in R. Topics include residual analysis, maximum likelihood methods, graphical presentations, ordinary least squares, model II regression, transformations, model selection with focus on information-theoretic approaches and outlier detection.

Three term hours, fall, every year.


BIOL 864: Introduction to Mixed Effects Models for Biological Data

The course will focus on the use of mixed models that include random effects for biological data. Topics will include partitioning of random variance, nested, partially-nested and repeated-measures experimental designs, and modern approaches to evaluating competing models. Students will gain in-depth experience using R, a Language and Environment for Statistical Computing.

Three term hours, fall, every year.


BIOL 865: Advanced Statistical Analysis of Biological Data

A course in advanced statistical techniques for biological data. Possible topics include comparative methods, phylogenetic analysis, general addictive models, nonlinear regression, network analysis, time series analysis, resampling, path analysis. Topics covered will depend upon student and faculty interests,

Three term hours, winter, every year.


Economics Department


ECON 852: Quantitative Methods

A first course in econometrics at the graduate level. Students are expected to have had at least one econometrics course at the undergraduate level, and to be familiar with matrix algebra and elementary statistics. A broad range of econometrics models will be covered.

Offered jointly with ECON 450