Aditya Guntuboyina (Instructor)
- Office Hours: Tue and Thu 1:30-2:30 pm (Evans 422)
- aditya@stat
.berkeley .edu
Dohyeong Ki (GSI)
- Office Hours: Friday 9-10 am, 1-2 pm, 5-6 pm (Evans 446)
- dohyeong
_ki@berkeley .edu
Syllabus¶
Basic information about the course can be found in the syllabus.
Schedule¶
| Jan 21 | Lecture 1 | Slides--Introduction and Overview | |
| Jan 23 | Lecture 2 | Notes--Simple Linear Regression (Frequentist Inference) | |
| Jan 24 | Lab part 1 | Notebook--Fitting Trends via Linear Regression | |
| Dataset 1 | US Population (from FRED) | ||
| Dataset 2 | USA Accidental Deaths (inbuilt dataset in R) | ||
| Lab part 2 | Notes--Normal Mean Inference |
| Jan 28 | Lecture 3 Notes | Notes--Simple Linear Regression (Bayesian Inference) | |
| Lecture 3 Code | Notebook--More on fitting trends via linear regression | ||
| Jan 30 | Lecture 4 Notes | Notes--Bayesian inference in linear regression | |
| Lecture 4 Code | Notebook--Uncertainty Quantification in Linear Regression | ||
| Jan 31 | Lab 2 | Notebook--Regression Details |
| Feb 4 | Lecture 5 Notes | Notes--Nonlinear Regression (Sinusoidal Model) | |
| Lecture 5 Code | Notebook--Sinusoidal Model Fitting | ||
| Dataset 1 | Annual Sunspots (from https://www.sidc.be/SILSO/datafiles) | ||
| Feb 06 | Lecture 6 Notes | Notes--Sum of Squares and Periodogram | |
| Lecture 6 Code | Notebook--Sum of Squares and Periodogram | ||
| Dataset 1 | Audio Middle C file | ||
| Feb 07 | Lab 3 | Notebook--More on fitting sinusoidal models |
| Feb 11 | Lecture 7 Notes | Notes--Discrete Fourier Transform | |
| Lecture 7 Code | Notebook--Discrete Fourier Transform | ||
| Feb 13 | Lecture 8 Notes | Notes--DFT, Periodogram, Nonlinear Regression | |
| Lecture 8 Code | Notebook--Uses of the Periodogram | ||
| Feb 14 | Lab 4 | Notebook--More on Nonlinear Models |
| Feb 18 | Lecture 9 Notes | Notes--Change of Slope Models | |
| Lecture 9 Code | Notebook--Change of Slope (or Broken-Stick Regression Model) | ||
| Feb 20 | Lecture 10 Notes | Notes--High-dimensional linear regression | |
| Lecture 10 Code | Notebook--High dimensional regression -- Ridge and LASSO | ||
| Feb 21 | Lab 5 | Notebook--Change-point model |
| Feb 25 | Lecture 11 Notes | Notes--Smooth Trend Estimation | |
| Lecture 11 Code | Notebook--Smooth Trend Estimation | ||
| Feb 27 | Lecture 12 Notes | Notes--Bayesian regularization | |
| Lecture 12 Code | Notebook--Bayesian regularization | ||
| Feb 28 | Lab 6 | Notebook--High-dimensional regression for change-points |
| Mar 04 | Lecture 13 Notes | Notes--Sunspots and the Spectrum Model | |
| Lecture 13 Code | Notebook--Sunspots and the Spectrum Model | ||
| Mar 04 | Lecture 14 Notes | Notes--Three high-dimensional models | |
| Lecture 14 Code | Notebook--Three high-dimensional models | ||
| Mar 07 | Lab 7 | Notebook--Spectrum Model applied to a FRED dataset |
| Mar 11 | Lecture 15 Notes | Notes--Spectrum Model | |
| Lecture 15 Code | Notebook--Spectral Analysis | ||
| Mar 13 | Lecture 16 Notes | Notes--AutoRegressive Models | |
| Lecture 16 Code | Notebook--AutoRegressive Models | ||
| Mar 14 | Lab 8 | Notebook--Review for Midterm |