Fundamentals of Statistics II: Study Design and Data Collection Essentials

This is the 2nd workshop in a 5-part series focused on the fundamentals of statistics.

This webinar focuses on the first two crucial steps in a statistical investigation: 

1) identify a question and

2) collect the right data to answer this question. 

You will learn about:

• observational studies and experiments
• scope of inference
• various sampling strategies and their benefits/drawbacks
• key parts of experimental design (randomization, replication, blocking)
• power and sample size calculations

Check out the video below for a teaser from a previous session:

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 here for 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

Nikolas Krstic is a PhD graduate student at the Department of Statistics and a part-time Statistical Consultant with ASDa. While pursuing his previous degrees, he worked as a statistical analyst at the British Columbia Centre for Disease Control (BCCDC), authoring several published papers on a wide range of environmental health topics. Over the past couple of years, he has worked with numerous clients on projects from a variety of different disciplines. During his studies, research and consulting work, he has developed a strong background in regression analysis, spatial statistics and statistical learning.