Click on class name for slides, and if available panopto for recording

The course schedule is subject to change.

Week	Date	Lecture	Reading	Files	Lab
1	Sep 28	1 Introduction		[video][slide]
2	Oct 3	2 Probability and Statistics	Sec 1~3.2	[video][slide]
2	Oct 5	3 GitHub and Computing Resources	Instructions	[video][slide]
3	Oct 10	4 Moments and Transformation of variables	Sec 3.3~3.5	[video][slide]	Lab 1
3	Oct 12	5 Probability distribution and Measurement errors	Sec 3.6~4.2	[video][slide]	Lab 1
4	Oct 17	6 Error propagation and confidence level	Sec 4.3~4.5	[video][slide]	Lab 2
4	Oct 19	7 Monte Carlo Simulation I (Zoom)	Sec 5.1-5.2	[video][slide]	Lab 2
5	Oct 24	8 Monte Carlo Simulation II	Sec 5.3~5.4	[video][slide]	Lab 3
5	Oct 26	9 Career Panel (Zoom)		[video][gslide]	Lab 3
6	Oct 31	10 Parameter Inference I - Maximum Likelihood Estimator	Sec 6.1~6.5	[video][slide]	Lab 4
6	Nov 2	11 Parameter Inference II	Ch 7	[video][slide][quiz]	Lab 4
7	Nov 7	12 Final projets intro, hypothesis test & p-value (Zoom)	Sec 10.1~10.3	[video][slide][quiz]	Lab 5
7	Nov 9	13 Goodness of fit, significance (Zoom)	Sec 10.3-10.5	[video][slide][quiz]	Lab 5
8	Nov 14	14 Error Interval & error propagation	Sec 8.1-8.3	[video][slide]	Lab 6
8	Nov 16	15 Confidence Interval	Sec 8.4 Sec 13.6	[video][slide]	Lab 6
9	Nov 21	16 Upper limit	Sec 5.3 Luca Lista Sec 8 Eilam Gross	[video][slide]	No lab
9	Nov 23	No lecture			No lab
10	Nov 28	17 Expected sensitivity	Sec 5.6 Luca Lista Sec 4 Eilam Gross	[video][slide]	Lab 7 talk [A][B][C]
10	Nov 30	18 Principle Component Analysis	Ch11.1~11.3	[video][slide]	Lab 7 talk [A][B][C]
11	Dec 5	19 Classification	Ch11.4	[slide]	Lab 8
11	Dec 7	20 Summary		[video][slide]	Lab 8