Description:

Proper planning for quantitative research is a crucial and sometimes overlooked step in the research process. Studies with sample sizes that are too small to have a good chance of finding realistic effects waste time and effort and can increase the likelihood of incorrect conclusions. This workshop will review basic concepts for hypothesis testing, statistical power, and precision analysis and help participants understand what they need to know to properly plan their statistical analyses with appropriate sample sizes. It will include a short demonstration using R software for power analysis.

Prerequisites: Participants should be familiar with basic statistical concepts and methods like those taught in an introductory statistics course.

This workshop complements our other data science services and support for researchers. All Northwestern researchers (student, staff, and faculty in all fields) can request free consultations with our Data Scientists and Statisticians to guide you through your data project, from considering the feasibility and choosing a method to troubleshooting the code and suggesting improvements. If you're looking for more extensive support, we partner on faculty-sponsored research through our project collaboration service.