Summer School in Statistics for Astronomers XVI (June 1 – 5, 2021)
Virtual meeting via Zoom.
Presentations will be recorded, and will be accessible to the participants.
Each day the program starts at 10:30am EDT and ends at 4pm EDT.
The times below are based on Eastern Daylight saving Time (EDT = UTC-04:00).
The times below are based on Eastern Daylight saving Time (EDT = UTC-04:00).
| June 1, 2021 (Tuesday) | |
|---|---|
| 10:30 a.m. – 10:40 a.m. | Welcome address (Jogesh Babu) |
| 10:40 a.m. – 1:00 p.m. | Probability (David Hunter) |
| 30 Min Break | |
| 1:30 p.m. – 2:45 p.m. |
Inference I (Hyungsuk Tak) |
| 15 Min Break | |
| 3:00 p.m. – 3:30 p.m. | Astrostatistics: Past, Present, and Future (Eric Feigelson) |
| 3:30 p.m. – 4:00 p.m. | Introduction to R (Eric Feigelson) LAB Datasets: COMBO17_lowz.dat, SDSS_QSO.dat, SDSS_stars.csv, SDSS_test.csv, SDSS_wd.csv, GX.dat, Kepler1.dat, Kepler2.dat, NGC4472_profile.dat |
| June 2, 2021 (Wednesday) | |
|---|---|
| 10:30 a.m. – 11:45 a.m. | Inference II (Hyungsuk Tak) |
| 15 Min Break | |
| 12:00 p.m. – 1:00 p.m. | Model Fitting & Bootstrap (G. Jogesh Babu) |
| 40 Min Break | |
| 1:40 p.m. – 3:15 p.m. | Regression (Chad Schafer) |
| 15 Min Break | |
| 3:30 p.m. – 4:00 p.m. |
R session for Astronomy II (Eric Feigelson) LAB |
| June 3, 2021 (Thursday) | |
|---|---|
| 10:30 a.m. – 12:20 p.m. | Multivariate Analysis, Clustering, and Classification (Chad Schafer) |
| 40 Min Break | |
|
1:00 p.m. – 3:15 p.m. |
Introduction to Bayesian Inference (Thomas Loredo) |
| 15 Min Break | |
| 3:30 p.m. – 4:00 p.m. |
R tutorial: Regression (Eric Feigelson) LAB
|
| June 4, 2021 (Friday) | |
|---|---|
| 10:30 a.m. – 12:00 p.m. | Markov chain Monte Carlo (MCMC) (Murali Haran) |
| 30 Min Break | |
| 12:30 p.m. – 1:45 p.m. | Time Series Analysis (Eric Feigelson) |
| 15 Min Break | |
| 2:00 p.m. – 3:20 p.m. | Spatial Models: A Quick Overview (Murali Haran) |
| 10 Min Break | |
| 3:30 p.m. – 4:00 p.m. |
R tutorial: Clustering & Classification (Eric Feigelson) LAB |
| June 5, 2021 (Saturday) | |
|---|---|
| 10:30 a.m. – 1:10 p.m. | Deep Learning Neural Network (David Banks) |
| 40 Min Break | |
| 1:50 p.m. – 3:20 p.m. |
Machine Learning with Random Forest (Peter Freeman) |
| 10 Min Break | |
| 3:30 p.m. – 4:00 p.m. |
R tutorial: Time Series (Eric Feigelson) LAB
|
INSTRUCTORS: G. Jogesh Babu, Murali Haran, David Hunter, and Hyungsuk Tak (Statisticians, Penn State); Eric Feigelson (Astronomer, Penn State); Chad Schafer, and Peter Freeman (Statisticians, Carnegie Mellon University); David Banks (Statistician, Duke University); Thomas Loredo (Astronomer, Cornell University).