Biography
Dr. Larose's expertise ranges from predictive analytics, through data science, missing data analysis, and R programming. She loves to find the story behind the data. In the classroom, her objective is to inspire students to love statistical analysis as much as she does, whether the students are math-whizzes or math-phobes. Her Ph.D. in Statistics is from UConn, Storrs, with the dissertation, “Model-Based Clustering of Incomplete Data.”
Research Interests
My recent research work has been in the areas of learning analytics, missing data, predictive analytics, and data science.
Of Note
Dr. Larose and her Statistics Ph.D. father Dr. Daniel T. Larose have recently co-authored their third textbook on data science. "Data Science using Python and R" will appear in 2019 (John Wiley and Sons, Inc.). She is also the winner of the national 2014 Student Research Competition award from the Applied Public Health Statistics section of the American Public Health Association.
Teaching Interests
- Statistics, Data Science, and Predictive Analytics
- Sports Statistics
- Anything that involves data analysis
Publications
Chantal Larose, Daniel Larose, "Data Science using Python and R". John Wiley & Sons, New York, 2019 (to appear).
Chantal Larose, Kim Ward, "Real-World Learning Analytics: Modeling Student Academic Practices and Performance". In JSM Proceedings. Alexandria, VA: American Statistical Association (to appear).
Chantal Larose, Dipak Dey, Ofer Harel, "The Impact of Missing Values on Different Measures of Uncertainty". Accepted at Statistica Sinica, doi:10.5705/ss.202016.0073.
Marsha Davis, Chantal Larose, "Classification Using CART Models". HiMAP Pull-out Section in COMAP: Consortium for Mathematics and Its Applications, Fall / Winter 2018, 9 - 24.
Daniel Larose, Chantal Larose, Data Mining and Predictive Analytics. John Wiley & Sons, New York, 2015.
https://www.linkedin.com/in/chantal-larose-48923745/
Personal Webpage
