# Mine Çetinkaya-Rundel

Education:

- PhD in Statistics (2011), University of California, Los Angeles, Department of Statistics

- M.S. in Statistics (2008), University of California, Los Angeles, Department of Statistics

- B.S. in Actuarial Science (2004), New York University, Leonard N. Stern School of Business

Research interests:

- Teaching and education

- Statistics pedagogy

- Spatial statistics

- Small area estimation

- Survey and public health data

Aug 28th 2017

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 summary statistics and basic data visualization.

Aug 28th 2017

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 score for a child based on certain characteristics of his or her mother? In this course, you will learn the fundamental theory behind linear regression and, through data examples, learn to fit, examine, and utilize regression models to examine relationships between multiple variables, using the free statistical software R and RStudio.

Aug 21st 2017

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.

Sep 14th 2015

This course introduces you to the discipline of statistics as a science of understanding and analyzing data. You will learn how to effectively make use of data in the face of uncertainty: how to collect data, how to analyze data, and how to use data to make inferences and conclusions about real world phenomena.

Oct 6th 2014

We prepare high school teachers for teaching descriptive statistics. Teachers will learn basic principles for summarizing data in meaningful ways. Satellite videos will discuss pedagogy and teach statistical software via examples spanning pop culture, sports, health and other topics suitable for high school classrooms.