All resampling techniques are based on the idea of repeatedly estimating a statistic based on subsets of the sample.
There are many practical applications, including estimating standard errors when they can’t be based on a theoretical distribution (a.k.a., when distributional assumptions are not met).
In this webinar, we’ll talk about some of the most common resampling techniques, including the jacknife and bootstrap, how they work, and situations in which they’re useful.
Note: This training is an exclusive benefit to members of the Statistically Speaking Membership Program and part of the Stat’s Amore Trainings Series. Each Stat’s Amore Training is approximately 90 minutes long.
About the Instructor
Karen Grace-Martin helps statistics practitioners gain an intuitive understanding of how statistics is applied to real data in research studies.
She has guided and trained researchers through their statistical analysis for over 15 years as a statistical consultant at Cornell University and through The Analysis Factor. She has master’s degrees in both applied statistics and social psychology and is an expert in SPSS and SAS.
You'll get access to this training webinar, 130+ other stats trainings, a pathway to work through the trainings that you need — plus the expert guidance you need to build statistical skill with live Q&A sessions and an ask-a-mentor forum.