On this episode, I am joined by Dr. Jason Osborne, Associate Provost and Dean of the Graduate School at Clemson University in Clemson, SC, where he is also Professor of Applied Statistics in the Department of Mathematical Sciences and in Public Health Sciences. He is author of over 70 peer-reviewed articles and seven books, many of which focus on best practices in statistical methods. He has also been active in research related to social justice, educational psychology, and evaluation. His work has been cited in scholarly publications over 10,000 times according to Google Scholar, and he is also an Accredited Professional Statisticiantm (awarded by the American Statistical Association). Jason is a 3rd degree black belt in Songahm Tae Kwon Do, and the proud father of three, each of which he considers an outlier in the positive tail of the distribution of awesomeness.
Segment 1: Data cleaning [00:00-11:35]
In this first segment, Jason talks about what constitutes data cleaning and why data cleaning practices are so important to do before data analysis takes place.
Segment 2: Myths and practicalities of data cleaning [11:36-22:59]
In segment two, Jason discusses some of the pervasive myths of data cleaning and debunks the myths based on his book Best Practices in Data Cleaning.
Segment 3: Jason's current and upcoming projects [23:00-33:15]
In segment three, Jason shares about his new book on regression and his focus on mentoring readers into a larger regression universe.
Bonus Clip # 1: Assumptions of Measurement [00:00-2:22]
Bonus Clip # 2: Methods for Testing Assumptions [00:00-5:43]
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