The Principles of Biostatistics course is offered by One Health at UCalgary in collaboration with the University of Calgary Biostatistics Center

This course is comprised of two sections:

Section 1: Fundamentals of Biostatisticswill serve as a fundamental foundation for participants to understand the basic concepts of biostatistics with a focus on statistical testing in research studies.

Section 2: Applied Statistical Modelling for Data Analysis in R, will cover basics of applied statistical modelling.  

Course Overview

Date: May 9-June 3, 2022 | 57 hours in total, Non-credit

Section 1: May 9-20, 2022 | 30 hours (15 hours lecture + 15 hours lab)

Section 2: May 24-June 3, 2022 | 27 hours (13.5 hours lecture + 13.5 hours lab)

Format of delivery: Virtual

Time: Monday-Friday 1:00-4:00 PM (MDT) 

  • Lecture section: 1:00-2:30 PM
    • Course material will be delivered live and instructors will answer students’ questions.
  • Hands-on component: 2:30-4:00 PM 
    • Students will work with a lab instructor in R studio to gain practical skills in implementing the concepts covered during the lecture. The instructor will spend a portion of the class demonstrating the necessary skills and then will be available to assist students in solving a variety of problems with the software.

Audience: Open to domestic and international students (undergraduate, graduate, and post-doctoral fellows), professionals and adult learners.

Eligibility: Background knowledge in Fundamental Statistics is highly recommended to understand the topics thoroughly, especially for those who plan to sign up for session 2 only.

Ability to understand and communicate in English is required.

Required Software: R and RStudio software (free to download).

Certificate:  An electronic certificate of participation will be given to attendees upon completion of the course.

Maximum No. of participants in each section: 25 

Fee: $300 CAD for each section

Refund Policy: 

  • Participants must submit an email notice to onehealth@ucalgary.ca at least 7 business days before the course start date.
  • Submit a refund request on Eventbrite
  • There will be $15 administration fee deducted. 

Deadline to register:

  • Section 1: May 8, 2022 at 8:pm (MT) 
  • Section 2: May 23, 2022 at 8:pm (MT) 

Topics

Module 1: Introduction to Statistics

  • Data collection and sampling methods
  • Data classification and presentation
  • Measure of central tendency and variability

Module 2: Statistical Inference

  • Tests/confidence intervals for one group
  • Tests/confidence intervals for two group comparisons
  • Test for multiple group comparisons (ANOVA) and post-hoc tests
  • Chi-square tests

Module 3: Introduction to Statistical Modelling with R

  • Simple linear regression

Module 4: Applied Statistical Modeling with R

  • Multiple Linear Regression Model Building (First order model/Model with interaction/Higher order model) for quantitative and qualitative independent variables
  • Estimation and Interpretation of the model parameters
  • Significance Testing (Full model test /Partial test)
  • Model Selections (Stepwise/Backward/Forward Procedure)
  • Model Diagnostics (Linearity/Independence/Normality/Homoscedasticity/Outliers)
  • Model Transformation (Box Cox Transformation) 
  • Model Prediction

Learning Outcomes

At the end of this section, participants will be able to: 

  • Apply the basic principles of biostatistics to summarize and draw conclusions from data.
  • Formulate testable research questions, evaluate the suitability of different research designs, plan a well-designed experiment or clinical trial, choose an appropriate statistical test and present results in a scientific and comprehensible manner.

  • Implement R-software and analyze statistical results for biomedical and veterinary data.

At the end of this section, participants will be able to: 

  • Model the multiple linear relationship between a response variable (Y) and all explanatory variables (both categorical and numerical variables) with interaction terms.  Interpret model parameter estimates, construct confidence intervals for regression coefficients, evaluate model fits, visualize correlations between a response variable (Y) and all explanatory variables (X) by graphs (scatter plot, residual plot) to assess model validity.
  • Predict the response variable at a certain level of the explanatory variables, once the fit model exists.
  • Implement R-software and analyze statistical results for biomedical and veterinary data.

Assessment

Assignments will be posted on Slack (our communication tool with students). 

Students must attend 70% of the sessions in order to receive the certificate and are encouraged to work on the assignments progressively throughout the course as the relevant material is covered.

Assignments will be posted on Slack (our communication tool with students). 

Students must attend 70% of the sessions in order to receive the certificate and are encouraged to work on the assignments progressively throughout the course as the relevant material is covered.


Instructors

Katie Burak

Katie Burak 

Section 1 Instructor 

University of Alberta 

kburak@ualberta.ca

View Bio

Thuntida Ngamkham

Dr. Thuntida Ngamkham

Section 2 Instructor 

University of Calgary 

thuntida.ngamkham@ucalgary.ca

View Bio

Anne Bian

Anne Bian

Section 1 Lab Instructor 

University of Calgary 

jiayi.bian@ucalgary.ca

View bio

 

Mili Roy

Mili Roy

Section 2 Lab Instructor 

University of Calgary 

roym@ucalgary.ca

View bio

 

Ann H from Pexels

If you have any questions or need assistance regarding the Principles of Biostatistics course, please contact onehealth@ucalgary.ca

Thank you!