Brenda Gunderson

Brenda Gunderson received her PhD in Statistics from The University of Michigan in 1989. She has stayed on at UM and is a Senior Lecturer. She coordinates and teaches the largest undergraduate statistics course, Statistics and Data Analysis, with approximately 1800 students each term. She is also an undergraduate advisor for students electing to major or minor in Statistics. Her research focuses on Statistical Education, in particular using technology to enhance teaching and learning. Brenda received the UM Teaching Innovation Prize for her work on Infusing Technology for Guided Continuous Learning in a Large Gateway Course. She is co-investigator for a UM grant called: Enhancing Undergraduate Education through the Deployment of Quality Learning Objects. Her work on this grant led to receiving the Innovative Use of MERLOT Award (2009) and a Sloan-C Effective Practice Award (2012). She is also part of an NSF project to expand the UM E2Coach system (Expert Electronic Coaching) to students in introductory statistics courses -- computer tailored communication technology allows us to provide individualized coaching and advice to students using their individual background, goals, and current standing in the course.

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Fitting Statistical Models to Data with Python (Coursera)

In this course, we will expand our exploration of statistical inference techniques by focusing on the science and art of fitting statistical models to data. We will build on the concepts presented in the Statistical Inference course (Course 2) to emphasize the importance of connecting research questions to our [...]
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Inferential Statistical Analysis with Python (Coursera)

In this course, we will explore basic principles behind using data for estimation and for assessing theories. We will analyze both categorical data and quantitative data, starting with one population techniques and expanding to handle comparisons of two populations. We will learn how to construct confidence intervals. We will [...]
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Understanding and Visualizing Data with Python (Coursera)

In this course, learners will be introduced to the field of statistics, including where data come from, study design, data management, and exploring and visualizing data. Learners will identify different types of data, and learn how to visualize, analyze, and interpret summaries for both univariate and multivariate data. Learners [...]
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