Mine Çetinkaya-Rundel

Mine Çetinkaya-Rundel is an Assistant Professor of the Practice at the Department of Statistical Science at Duke University. She received her Ph.D. in Statistics from the University of California, Los Angeles, and a B.S. in Actuarial Science from New York University's Stern School of Business. Dr. Çetinkaya-Rundel is primarily interested in innovative approaches to statistics pedagogy. Some of her recent work focuses on developing student-centered learning tools for introductory statistics courses, teaching computation at the introductory statistics level with an emphasis on reproducibility, and exploring the gender gap in self-efficacy in STEM fields. Her research interests also include spatial modeling of survey, public health, and environmental data. She is a co-author of OpenIntro Statistics and a contributing member of the OpenIntro project, whose mission is to make educational products that are open-licensed, transparent, and help lower barriers to education. She is also a co-editor of the Citizen Statistician blog and a contributor to the Taking a Chance in the Classroom column in Chance Magazine.

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Inferential Statistics (Coursera)

This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a way that is interpretable for clients or the public. Using numerous data examples, you [...]
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Linear Regression and Modeling (Coursera)

This course introduces simple and multiple linear regression models. These models allow you to assess the relationship between variables in a data set and a continuous response variable. Is there a relationship between the physical attractiveness of a professor and their student evaluation scores? Can we predict the test [...]
3
Average: 3 ( 4 votes )

Introduction to Probability and Data with R (Coursera)

This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule. You will examine various types of sampling methods, and discuss how such methods can impact the scope of inference. A variety of exploratory data analysis techniques will be covered, including numeric [...]
9
Average: 9 ( 4 votes )

Bayesian Statistics (Coursera)

This course describes Bayesian statistics, in which one's inferences about parameters or hypotheses are updated as evidence accumulates. You will learn to use Bayes’ rule to transform prior probabilities into posterior probabilities, and be introduced to the underlying theory and perspective of the Bayesian paradigm. [...]
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