Brady T. West

Brady T. West is a Research Associate Professor in the Survey Methodology Program, located within the Survey Research Center at the Institute for Social Research on the University of Michigan-Ann Arbor (U-M) campus. He earned his PhD from the Michigan Program in Survey Methodology in 2011. Before that, he received an MA in Applied Statistics from the U-M Statistics Department in 2002, being recognized as an Outstanding First-year Applied Masters student, and a BS in Statistics with Highest Honors and Highest Distinction from the U-M Statistics Department in 2001. His current research interests include the implications of measurement error in auxiliary variables and survey paradata for survey estimation, survey nonresponse, interviewer effects, and multilevel regression models for clustered and longitudinal data. He is the lead author of a book comparing different statistical software packages in terms of their mixed-effects modeling procedures (Linear Mixed Models: A Practical Guide using Statistical Software, Second Edition, Chapman Hall/CRC Press, 2014), and he is a co-author of a second book entitled Applied Survey Data Analysis (with Steven Heeringa and Pat Berglund), the second edition of which was published by Chapman Hill in June 2017. Brady lives in Dexter, MI with his wife Laura, his son Carter, his daughter Everleigh, and his American Cocker Spaniel Bailey.

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Inferential Statistical Analysis with Python (Coursera) Coursera
University of Michigan

Inferential Statistical Analysis with Python (Coursera)

Discover the power of Python in understanding data through inferential statistics. This course will guide you from basic principles to advanced techniques for analyzing both categorical and quantitative data, comparing populations, constructing confidence intervals, and testing theories using sample data. Perfect for beginners and professionals alike who want to harness the potential of statistical analysis with Python.

Jun 29th 2026
4 Weeks
The Total Data Quality Framework (Coursera) Coursera
University of Michigan

The Total Data Quality Framework (Coursera)

Discover the essential principles of the Total Data Quality Framework in this specialized online course. Designed for data enthusiasts and professionals alike, this course will guide you through understanding the differences between designed and gathered data, exploring the key dimensions of TDQ, and learning how to mitigate potential threats to data quality. Whether you're new to data management or looking to refine your expertise, this course offers valuable insights into ensuring high-quality data analysis.

Jun 22nd 2026
4 Weeks
Design Strategies for Maximizing Total Data Quality (Coursera) Coursera
University of Michigan

Design Strategies for Maximizing Total Data Quality (Coursera)

Maximize your data's potential with our 'Design Strategies for Maximizing Total Data Quality' course. This expert-led program will equip you with essential skills in designing effective data collection methods and techniques to enhance the quality of your data at every stage. Whether you're dealing with designed or found/organic data, this course provides actionable strategies to improve TDQ and make informed decisions based on reliable data.

Jun 22nd 2026
4 Weeks
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