mds:smd:start

**Salvatore Ruggieri**- Università di Pisa

**Office hours**- Tuesday h 14:00 - 17:00, Department of Computer Science, room 321/DO.
**Office hours only via skype. Skype contact: salvatore.ruggieri**

**Dates are preliminary.**

Day of Week | Hour | Room |
---|---|---|

Tuesday | 16:00 - 18:00 | |

Wednesday | 9:00 - 11:00 | |

Students should be comfortable with most of the topics on mathematical calculus covered in:

**[P]**J. Ward, J. Abdey.**Mathematics and Statistics**. University of London, 2013.*Chapters 1-8 of Part 1*.

Extra-lessons refreshing such notions may be planned in the first part of the course.

The following are *mandatory text books*:

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

- The project can be done in groups of at most 3 students.
- The project must be delivered (report + code) by end of July.
- The oral discussion must be done by the September session, and it will cover both the project and all topics of the course.
- The project replaces the written exam but
**students have to register for the written dates in order to fill the student's questionnaire**. - Groups ready to discuss send the project to the teacher plus availability time slots for oral discussion.
- Google Drive project directory (accessible only to authorized students)

* There are no mid-terms.* The exam consists of a written part and an oral part. The written part consists of exercises on the topics of the course. Each question is assigned a grade, summing up to 30 points. Students are admitted to the oral part if they receive a grade of at least 18 points. Written exam consists of open questions and exercises. Example written texts:

Registration to exams is mandatory (**deadline is 5 days before the exam!**): register here

Date | Hour | Room |
---|---|---|

24/7/2020 | 9:00 - 11:00 | Online exam |

7/9/2020 | 11:00 - 13:00 | Online exam |

**Distance-learning lessons**: see instructions for Google Meet and use the room code: 500PP.

Date | Room | Topic | Learning material | |
---|---|---|---|---|

1 | 25.02 16:00-18:00 | L1 | Introduction. Probability and independence. | [T] Chpts. 1-3 |

2 | 26.02 9:00-11:00 | A1 | R basics. | [R] Chpts. 1,2.1,2.2 slides script1.R |

3 | 03.03 16:00-18:00 | L1 | Discrete random variables. | [T] Chpt. 4 [R] Chpt. 3 script2.R |

4 | 04.03 9:00-11:00 | A1 | Continuous random variables. Simulation. | [T] Chpts. 5, 6.1-6.2 [R] Chpt. 3 script3.R |

5 | 10.03 16:00-18:00 | Distance-learning | Recalls: derivatives and integrals. rec01 audio-video (.flv) | [P] Chpt. 1-8 scriptMath.R |

6 | 11.03 9:00-11:00 | Distance-learning | Expectation and variance. R data access. rec02 audio-video (.flv) | [T] Chpt. 7 [R] Chpt. 2.4 script4.R |

7 | 17.03 16:00-18:00 | Distance-learning | R programming. Project presentation. rec03 audio-video (.flv) and project info audio-video (.flv) | [R] Chpt. 2.3 exercise.R script5.zip |

8 | 18.03 9:00-11:00 | Distance-learning | Project presentation. Power laws and Zipf laws. rec04 audio-video (.flv) | Newman's paper Sect I, II, III(A,B,E,F) script6.R |

9 | 24.03 16:00-18:00 | Distance-learning | Computations with random variables. Joint distributions. rec05 audio-video (.flv) | [T] Chpts. 8-9 script7.zip |

10 | 25.03 9:00-11:00 | Distance-learning | Covariance. Sum of random variables. rec06 audio-video (.flv) | [T] Chpts. 10-11 script8.R |

11 | 31.03 16:00-18:00 | Distance-learning | Law of large numbers. The central limit theorem. rec07 audio-video (.flv) | [T] Chpts. 13-14 script9.R |

12 | 1.04 9:00-11:00 | Distance-learning | Graphical summaries. rec08 audio-video (.flv) | [T] Chpt. 15 script10.R |

13 | 7.04 16:00-18:00 | Distance-learning | Numerical summaries. Data preprocessing in R. Q&A on the project. rec09 audio-video (.flv), project data audio-video (.flv) | [T] Chpt. 16, [R] Chpts. 4,10 script11.R, dataprep.R |

14 | 8.04 9:00-11:00 | Distance-learning | Unbiased estimators. Efficiency and MSE. rec10 audio-video (.flv) | [T] Chpts. 17.1-17.3, 19, 20 script12.R |

| No lesson on this date. Students work on the project on their own. | |||

15 | 21.04 16:00-18:00 | Distance-learning | Maximum likelihood. Fisher information.rec11 audio-video (.flv) | [T] Chpt. 21 notes1.pdf script13.R |

16 | 22.04 9:00-11:00 | Distance-learning | Simple linear and polynomial regression. Least squares. rec12 audio-video (.flv) | [T] Chpts. 17.4,22 [R] Chpts. 6,12.1 script14.R |

17 | 28.04 16:00-18:00 | Distance-learning | Multiple, non-linear, and logistic regression. rec13 audio-video (.flv) | [R] Chpt. 13,16.1-16.2 notes2.pdf script15.R |

18 | 29.04 9:00-11:00 | Distance-learning | Confidence intervals: Gaussian, T-student, large sample method. rec14 audio-video (.flv) | [T] Chpts. 23.1,23.2,23.4, 24.3,24.4 script16.R |

19 | 05.05 16:00-18:00 | Distance-learning | Confidence intervals in linear regression. Empirical bootstrap. Application to confidence intervals. rec15 audio-video (.flv) | [T] Chpts. 18.1,18.2,23.3 notes2.pdf script17.R |

20 | 06.05 9:00-11:00 | Distance-learning | Parametric bootstrap. Hypotheses testing. rec16 audio-video (.flv) | [T] Chpts. 18.3,25 script18.R |

21 | 12.05 16:00-18:00 | Distance-learning | One-sample t-test and application to linear regression. rec17 audio-video (.flv) | [T] Chpts. 26-27, [R] Chpts. 5.1,5.2 notes2.pdf script19.R |

22 | 13.05 9:00-11:00 | Distance-learning | Goodness of fit: chi-square, K-S. Fitting power laws. rec18 audio-video (.flv) | K-S script20.R |

| No lesson on this date. Students work on the project on their own. | |||

23 | 20.05 9:00-11:00 | Distance-learning | Hypotheses testing: F-test, comparing two samples. rec19 audio-video (.flv) | [T] Chpts. 28, [R] Chpts. 5.3-5.7 script21.R |

| No lesson on this date. Students work on the project on their own. | |||

24 | 27.05 9:00-11:00 | Distance-learning | Project tutoring. rec20 audio-video (.flv) |

mds/smd/start.txt · Ultima modifica: 10/07/2020 alle 10:25 (2 mesi fa) da Salvatore Ruggieri