Day1. Thu 9/28. Syllabus, hw1, notesforhw1. 
Day2. Tue 10/3. Peng4-6, 8, Irizarry1,3,4. 
Day3. Thu 10/5. Irizarry4-6, beginning of 7.  
Day4. Tue 10/10. Hw1 is due. Irizarry 7-10, beginning of notesforhw2. 
Day5. Thu 10/12. Irizarry22-23, Peng9, the rest of notesforhw2. 
Day6. Tue 10/17. Irizarry24,27. 
Day7. Thu 10/19. Lecture7notes. 
Day8. Tue 10/24. Finish lecture7notes, Irizarry28, 29. 
Day9. Thu 10/26. Irizarry30-31. 
Day10. Tue 10/31. Lecture10notes: sum of squared differences from observations for each gridpoint in C, kernel regression, vectors and matrices in C, calling C functions from C, running C from terminal, reading in from a file, computing integrals in C. 
Day11. Thu 11/2. Lecture11notes. dnorm and change of variables, matrices in C, python and mySQL references, studying bias in the sample SD and variance in R and C, gam. 
Day12. Tue 11/7. Lecture12notes: logistic regression in R, nonlinear regression in R, C++ in R, big data in R. 
Day13. Thu 11/9. Finish Lecture12notes: big data in R. Rickpython1to6. 
Day14. Tue 11/14. Finish Rickpython1to6. rickscraping. 
Day15. Thu 11/16. NO CLASS TUE 11/21! Rickpython7, rickpython8to9, lecture15notes: MLE, Hawkes processes and MLE. 
NO CLASS TUE 11/21 OR THU 11/23! 
Day16. Tue 11/28. Newton-Raphson optimization, building R packages, projects reminder.