Dr. Jennifer Broatch is an Associate Professor of Statistics at Arizona State University. She received her Ph.D. in Statistics at Arizona State University in 2009. Dr. Broatch has led and contributed to multiple NSF-funded projects aimed at improving STEM and data-science education, curriculum development, educational evaluation, and research experiences for undergraduates. Her research spans statistical methodology, with a particular emphasis on modeling complex dependency structures, utilizing generalized linear mixed models, with applications in public health, conservation biology, and educational evaluation. She also advances innovative pedagogical approaches to statistics education, focusing on improving conceptual understanding and data literacy across disciplines. Dr. Broatch was the inaugural recipient of ASU's Provost Teaching Award in 2023 and a nationally recognized leader in statistics curriculum reform. She is the lead author of Introductory Statistics: Analyzing Data with Purpose, developed with UT-Austin’s Charles A. Dana Center.
Dr. Jennifer Broatch is an Associate Professor of Statistics at Arizona State University. She received her Ph.D. in Statistics at Arizona State University in 2009. Dr. Broatch has led and contributed to multiple NSF-funded projects aimed at improving STEM and data-science education, curriculum development, educational evaluation, and research experiences for undergraduates. Her research spans statistical methodology, with a particular emphasis on modeling complex dependency structures, utilizing generalized linear mixed models, with applications in public health, conservation biology, and educational evaluation. She also advances innovative pedagogical approaches to statistics education, focusing on improving conceptual understanding and data literacy across disciplines. Dr. Broatch was the inaugural recipient of ASU's Provost Teaching Award in 2023 and a nationally recognized leader in statistics curriculum reform. She is the lead author of Introductory Statistics: Analyzing Data with Purpose, developed with UT-Austin’s Charles A. Dana Center.