Fundamentals of Statistics IV: Correlation and Linear Regression

This is the 4th workshop in a 5-part series focused on the fundamentals of statistics.

Understanding relationships is a key part of the scientific inquiry process. You will learn how to describe relationships between two numerical quantities through correlation measures and simple linear regression models. This will also be extended to multiple linear regression for including additional predictor variables. 

Specific topics include:

• correlation vs causation
• interpretation of regression model coefficients
• assessing the “fit” of a model
• model selection

Check out the video below for a teaser from a previous session: https://www.youtube.com/watch?v=KVzGCfjbRCQ

More on this series

This webinar series was made possible via joint collaboration between Applied Statistics and Data Science Group and Graduate Pathways for Success Program, funded by the Graduate Pathways for Success Program.

Statistics is a scientific discipline that enables reaching meaningful conclusions from data. To produce reliable results, you need to justify the choice of the applied statistical methods and models as well as validate the underlying assumptions.

This webinar series provides an overview of foundational statistical concepts using examples of various data structures. We will discuss types of study designs, methods, models and appropriate application of statistical tests along with interpretations of the results obtained from different statistical tools. The aim is to equip the attendees with a deeper understanding of the key concepts of statistical methodology, rather than solving specific project problems or providing hands-on guidance.

Each webinar is a self-contained introduction to different statistical concepts, but as topics become increasingly complex with each consecutive webinar, some aspects will be built on concepts taught in the previous sessions. Hence, there is benefit in attending all the webinars.

If you are a graduate student and have questions about your specific project, please see the SOS Program to book a one-hour free statistical consultation.

ABOUT ASDA

The Applied Statistics and Data Science Group (ASDa) in the UBC Department of Statistics provides statistical consulting services and participates in collaborative research. ASDa expertise includes problem formulation, translation of research questions into testable statistical hypotheses, design of experiments and sampling plans for surveys, the choice and explanation of statistical methodology, statistical computing and graphics, the interpretation of findings and more. ASDa also plays an active role in continuing education on and off the UBC campus, giving seminars, webinars, hands-on workshops and courses on statistical concepts and methodologies to various departments, research groups and at teaching hospitals.

Facilitator

Biljana Jonoska Stojkova, PhD, is a Senior Statistical Consultant with ASDa, participating in collaborative research, providing statistical consulting services and tailored education on statistical concepts and analytics tools on and off campus, as well as participating in collaborative research. She completed her PhD in Statistics at SFU in 2017, where she focused on developing Bayesian algorithms and methods for multi-modal posterior spaces, which were applied to differential equation models, mixture Gaussian models, epidemiological and ecological models. In the previous roles she has gained experience with probabilistic models to determine different patterns of user behavior from chat messages, with development of relational databases and with machine learning algorithms such as supervised and unsupervised learning. In her consulting role Biljana continues to strengthen her skills in problem formulation, study design, grant proposal development, analysis and implementation, and continued education of non-statisticians on and off the UBC campus, giving webinars, workshops and courses on statistical concepts and methodology to various departments, research groups and at teaching hospitals.