June 3, 2024 (Monday)
10:00 a.m. – 11:00 a.m.	Introduction to Astrostatistics (Eric Feigelson, Penn State). Watch the lecture for 58 minutes.
11:10 a.m. – 2:20 p.m.	Probability (David Hunter, Penn State). Watch the lecture for 2 hours and 30 minutes.
2:20 p.m. – 2:50 p.m.	Live Q&A with David Hunter via Zoom
3:00 p.m. – 4:00 p.m.	Inference 1 (Hyungsuk Tak, Penn State). Watch the lecture for 1 hour (either shorter or longer version).

Homework: R Lab 1. Watch the recorded lecture and implement the tutorial.

 

June 4, 2024 (Tuesday)
10:00 a.m. – 11:40 a.m.	Inference 2 (Hyungsuk Tak, Penn State). Watch the lecture for up to 1 hour and 30 minutes.
11:50 a.m. – 12:20 p.m.	Live Q&A with Hyungsuk Tak via Zoom
12:30 p.m. – 3:00 p.m.	Regression (Ashley Villar, Harvard). Watch the lecture for 1 hour and 15 minutes.
3:00 p.m. –3:20 p.m	Live Q&A with Ashley Villar via Zoom
3:20 p.m. –4:00 p.m	Model fitting, bootstrap, model selection (Jogesh Babu, Penn State). Watch the lecture for 30 minutes.

 

June 5, 2024 (Wednesday)
10:00 a.m. – 10:20 a.m.	Live Q&A with Jogesh Babu via Zoom
10:20 a.m. – 1:40 p.m.	Supervised and unsupervised learning (Ashley Villar, Harvard). Watch the lecture for 1 hour and 2 minutes.
1:40 p.m. – 2:00 p.m.	Live Q&A with Ashley Villar via Zoom
2:00 p.m. – 4:00 p.m.	Bayesian 1 (Tom Loredo, Cornell). Watch the lecture for 1 hour and 50 minutes.

 

June 6, 2024 (Thursday)
10:00 a.m. – 10:50 a.m.	Bayesian 2 (Tom Loredo, Cornell). Watch the lecture for 50 minutes.
11:00 a.m. – 11:30 a.m.	Live Q&A with Tom Loredo via Zoom
11:30 a.m. – 1:40 p.m.	Parallel Session 1: Markov chain Monte Carlo (Murali Haran, Penn State). Watch the lecture for 1 hour and 10 minutes. Parallel Session 2: Time series (Eric Feigelson, Penn State). Watch the lecture for 1 hour and 15 minutes.
1:40 p.m. – 2:00 p.m.	Live Q&A with Eric Feigelson via Zoom. Murali Haran is not available for the live Q&A, so please use Slack to ask questions.
2:10 p.m. – 3:40 p.m.	Parallel Session 1: Nested sampling (Joshua Speagle, Univ. of Toronto). Watch the lecture for 1 hour and 20 minutes. Parallel Session 2: Spatial statistics (Murali Haran, Penn State). Watch the lecture for 1 hour and 20 minutes.
3:40 p.m. – 4:00 p.m.	Live Q&A with Joshua Speagle via Zoom. Murali Haran is not available for the live Q&A, so please use Slack to ask questions.

 

June 7, 2024 (Friday)
10:00 a.m. – 1:10 p.m.	Deep learning neural network (David Banks, Duke). Watch the lecture for 2 hours and 36 minutes.
1:10 p.m. – 1:40 p.m.	Live Q&A with David Banks via Zoom
1:50 p.m. – 3:30 p.m.	Parallel Session 1: Gaussian process (Suzanne Aigrain, Oxford). Watch the lecture for 1 hour and 25 minutes. Parallel Session 2: Machine learning with random forest (Peter Freeman, Carnegie Mellon). Watch the lecture for 1 hour and 25 minutes.
3:40 p.m. – 4:00 p.m.	Live Q&A with Peter Freeman via Zoom. Suzanne Aigrain is not available for the live Q&A, so please use Slack to ask questions.

 Instructors

• Suzanne Aigrain (Oxford University)

• Jogesh G. Babu (Penn State University)

• David Banks (Duke University)

• Eric Feigelson (Penn State University)

• Peter Freeman (Carnegie Mellon University)

• Murali Haran (Penn State University)

• David Hunter (Penn State University)

• Tom Loredo (Cornell University)

• Joshua Speagle (University of Toronto)

• Hyungsuk Tak (Penn State University)

• Ashley Villar (Harvard University)

Online TA Office Hours via Zoom

• 11:00 a.m. – 1:00 p.m. (EST): Omar Hagrass

• 1:00 p.m. – 3:00 p.m. (EST): Andrew Pellegrino

• 3:00 p.m. – 5:00 p.m. (EST): Kihyun Han

• 7:00 p.m. – 9:00 p.m. (EST): Manoj Wickramasinghage