mds:smd:2017

# Statistical Methods for Data Science A.Y. 2016/17

## Instructors

• Fabrizio Lillo
• QUANT Lab, Scuola Normale Superiore
• Salvatore Ruggieri
• KDD Lab, Università di Pisa

## Classes

Day of Week Hour Room
Monday 16:00 - 18:00 Fib-N1
Tuesday 9:00 - 11:00 Fib-H-Lab

## Office hours

• Prof. Lillo: Thursday h 16:00 - 18:00, Scuola Normale Superiore (please send an email in advance)
• Prof. Ruggieri: Tuesday h 14:00 - 17:00, Department of Computer Science, room 321/DO.

## Text Books

• [B1] F.M. Dekking C. Kraaikamp, H.P. Lopuha, L.E. Meester. A Modern Introduction to Probability and Statistics. Springer, 2005.
• [B2] P. Dalgaard. Introductory Statistics with R. 2nd edition, Springer, 2008.

## Written exam

Written exam consists of open questions and exercises. Example text: sample1, sample2. The exam lasts 2 hours. No teaching material can be consulted during the exam.

Registration is mandatory.

Date Hour Room
15/1/2018 14:00 - 16:00 Fib-L1
12/2/2018 14:00 - 16:00 Fib-L1

## Class calendar

Day Room Topic Learning material Instructor
1. 20.02 16:00-18:00 N1 Introduction. Probability and independence. [B1] Chpts. 1-3 F. Lillo
2. 21.02 9:00-11:00 H-Lab Discrete and continuous random variables. [B1] Chpts. 4-5 F. Lillo
3. 27.02 16:00-18:00 N1 R basics. [B2] Chpts. 1,2.1,2.4 slides script1.R S. Ruggieri
4. 28.02 9:00-11:00 H-Lab Simulation. Expectation and variance [B1] Chpts. 6-7 noteSim F. Lillo
5. 06.03 16:00-18:00 N1 R basics and distributions. [B2] Chpts. 2.2,3-4 script2.R S. Ruggieri
6. 07.03 9:00-11:00 H-Lab Computations with random variables. Covariance [B1] Chpts. 8-10 F. Lillo
7. 13.03 16:00-18:00 N1 Sum of random variables. Law of large numbers [B1] Chpts. 11,13 F. Lillo
8. 14.03 9:00-11:00 H-Lab R programming and graphics. [B2] Chpts. 2.3,3-4 exercise.R script3.R S. Ruggieri
9. 20.03 16:00-18:00 N1 The central limit theorem. Graphical summaries [B1] Chpts. 14,15 F. Lillo
10. 21.03 9:00-11:00 H-Lab Numerical summaries. Poisson process [B1] Chpts. 12,16 Rcode slidesF. Lillo
11. 27.03 16:00-18:00 N1 Unbiased estimators. Efficiency and MSE [B1] Chpts. 17,19, 20 F. Lillo
12. 28.03 9:00-11:00 Sem. Est Examples on CLT and MSE. Data preprocessing. [B2] Chpt. 10 dataprep.r script4.R S. Ruggieri
13. 03.04 16:00-18:00 N1 Maximum likelihood. [B1] Chpt. 21 fisher F. Lillo
14. 04.04 9:00-11:00 H-Lab Expectation-Maximization. Confidence Intervals. [B1] Chpt. 23 EMF. Lillo
15. 24.04 16:00-18:00 N1 No lesson.
16. 02.05 9:00-11:00 H-Lab Firm growth. Confidence Intervals (2) [B1] Chpt. 23 F. Lillo
17. 08.05 16:00-18:00 N1 Recap and power-laws Newman's paper, script5.R S. Ruggieri
18. 09.05 9:00-11:00 H-Lab Project data GDrive directory S. Ruggieri
19. 15.05 16:00-18:00 N1 Bootstrap. Hypotheses testing [B1] Chpts. 18,24,25 F. Lillo
20. 16.05 9:00-11:00 H-Lab Hypotheses testing. t and F test [B1] Chpts. 26,27, 28 F. Lillo
21. 22.05 16:00-18:00 N1 Hypotheses testing (correlation, K-S, chi-square) CorrNotes K-S F. Lillo
22. 23.05 9:00-11:00 H-Lab Hypotheses testing. Bootstrap. Intermediate project task. [B2] Chpt. 5.1, script6.R S. Ruggieri
23. 29.05 16:00-18:00 N1 Elements of linear time series analysis TimeSeries F. Lillo
24. 30.05 9:00-11:00 H-Lab Hypotheses testing, parameter estimation. [B2] Chpts. 5.2-5.7, 6, script7.R S. Ruggieri
mds/smd/2017.txt · Ultima modifica: 24/02/2021 alle 15:47 (7 settimane fa) da Salvatore Ruggieri