Courses

Below is a listing of the Department of Statistics Courses for Fall term 2018. The Statistics Department also offers some courses Online.

 
Fall Course Title Instructor Day(s) Time(s) Location
Stat 91r Supervised Reading &
Research
Mike Parzen TBD    
Stat 99r Tutorial – Senior Year Joe Blitzstein       
Stat 104 Introduction to Quantitative Methods for Economics Mike Parzen MWF 10:30 - 11:45 AM  
Stat 110 Introduction to Probability Joe Blitzstein  MW 1:30 - 2:45 PM   
Stat 120 Applied Bayesian Inference  Shaoyang Ning MW 10:30 - 11:45 AM   
Stat 121A Data Science 1 Kevin Rader & Pavlos Protopapa MW 1:30 - 2:45 PM  
Stat 131 Time Series and Prediction Pierre Jacob TuTh 9:00 - 10:15 AM  
Stat 139 Linear Models Kevin Rader MW 9:00 - 10:15 AM  
Stat 186/Gov2002 Causal Inference Kosuke Imai TuTh 1:30 - 2:45 PM  
Stat 195 Intro to Statistical Machine Learning Lucas Janson MW 4:30 - 5:45 PM  
Stat 210 Probability 1 Joe Blitzstein  TuTh 1:30 - 2:45 AM  
Stat 211 Statistical Inference 1 Lucas Janson MW 3:00 - 4:15 PM  
Stat 221

Monte Carlo Methods &

other Computational Tools for Statistical Learning

Jun Liu MW 3:00 - 4:15 PM  
Stat 230 Multivariate Statistical Analysis Samuel Kou MW 10:30 - 11:45 AM  
Stat 244 Linear & Generalized Linear Models Mark Glickman TuTh 12:00 - 1:15 PM  
Stat 300 Research in Statistics Natesh Pillai & Neil Shephard W 12:00- 1:15 PM  
Stat 303hf The Art & Practice of Teaching Statistics Xiao-Li Meng & Tracy Ke Tu 3:00 - 4:15 PM  
Stat 310  Topics in Astrostatistics Xiao-Li Meng and Friends Tu 12:00 - 1:15 PM  
Stat 314hfr Timely Topics in Statistics (Colloquium) Lucas Janson & Tracy Ke M 12 - 1:15 PM  
Stat 317 Computational Optimal Transport Pierre Jacob Th 10- 11:30AM  

 

 

*Course Schedules Tentative

PDF Download:
Fall 2018 Course List

My.Harvard Course Listings:
View Statisitcs Courses on My.Harvard

 

blitzstein


The Statistics probability course (STAT 110) is offered as an online course and is taught by Professor of the Practice Joseph Blitzstein. Joe Blitzstein has taught this course each year since 2006.
See the course on YouTube (available now) or at edX


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