mds:smd:start

**This course is discontinued. Starting from A.Y. 2021/22, it has been replaced by a 9 ECTS version:**

**Salvatore Ruggieri**- Università di Pisa

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

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

Tuesday | 16:00 - 18:00 | Teams Virtual Room |

Wednesday | 9:00 - 11:00 | Teams Virtual Room |

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 4 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.

* 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 (**beware of the registration deadline!**): register here

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

01 | 16.02 16:00-18:00 | Teams | Introduction. Probability and independence. rec01 audio-video (.mp4) | [T] Chpts. 1-3 slides01 (.pdf) |

02 | 23.02 16:00-18:00 | Teams | R basics. rec02 audio-video (.mp4) | [R] Chpts. 1,2.1,2.2 slides02 (.pdf), script02 (.R) |

03 | 24.02 9:00-11:00 | Teams | Discrete random variables. rec03 audio-video (.mp4) | [T] Chpt. 4 [R] Chpt. 3 slides03 (.pdf), script03 (.R) |

04 | 02.03 16:00-18:00 | Teams | Recalls: derivatives and integrals. rec04 audio-video (.mp4) | [P] Chpt. 1-8 slides04 (.pdf), script04 (.R) |

05 | 03.03 9:00-11:00 | Teams | Continuous random variables. Simulation. rec05 audio-video (.mp4) | [T] Chpts. 5, 6.1-6.2 [R] Chpt. 3 slides05 (.pdf), script05 (.R) |

06 | 09.03 16:00-18:00 | Teams | Expectation and variance. Computations with random variables. rec06 audio-video (.mp4) | [T] Chpts. 7,8 slides06 (.pdf), script06 (.R) |

07 | 10.03 9:00-11:00 | Teams | R data access and programming. rec07 audio-video (.mp4) | [R] Chpt. 2.3,2.4 script07 (.zip) |

08 | 16.03 16:00-18:00 | Teams | Power laws and Zipf laws. rec08 audio-video (.mp4) | Newman's paper Sect I, II, III(A,B,E,F) slides08 (.pdf), script08 (.zip) |

09 | 17.03 9:00-11:00 | Teams | Moments, joint distributions, sum of random variables. rec09 audio-video (.mp4) | [T] Chpts. 9-11 slides09 (.pdf), script09 (.zip) |

10 | 23.03 16:00-18:00 | Teams | Law of large numbers. The central limit theorem. rec10 audio-video (.mp4) | [T] Chpts. 13-14 slides10 (.pdf), script10 (.R) |

11 | 24.03 9:00-11:00 | Teams | Project presentation. Graphical summaries. rec11 audio-video (.mp4) | [T] Chpt. 15 slides11 (.pdf), script11 (.R) |

12 | 30.03 16:00-18:00 | Teams | Numerical summaries. Data preprocessing in R. rec12 audio-video (.mp4) | [T] Chpt. 16, [R] Chpts. 4,10 slides12 (.pdf), script12 (.R), dataprep.R |

13 | 7.04 9:00-11:00 | Teams | Unbiased estimators. Efficiency and MSE. rec13 audio-video (.mp4) | [T] Chpts. 17.1-17.3, 19, 20 slides13 (.pdf), script13 (.R) |

14 | 13.04 16:00-18:00 | Teams | Maximum likelihood estimation. rec14 audio-video (.mp4) | [T] Chpt. 21 notes1.pdf slides14 (.pdf), script14 (.R) |

15 | 14.04 9:00-11:00 | Teams | Linear regression. Least squares estimation. rec15 audio-video (.mp4) | [T] Chpts. 17.4,22 [R] Chpts. 6 notes2.pdf slides15 (.pdf), script15 (.R) |

16 | 20.04 16:00-18:00 | Teams | Multiple, non-linear, and logistic regression. rec16 audio-video (.mp4) | [R] Chpt. 12.1,13,16.1-16.2 notes2.pdf slides16 (.pdf), script16 (.zip) |

17 | 21.04 9:00-11:00 | Teams | Logistic regression (ctd). Introduction to confidence intervals. rec17 audio-video (.mp4) | [T] Chpts. 23.1 slides17 (.pdf), script17 (.R) |

18 | 27.04 16:00-18:00 | Teams | Confidence intervals: Gaussian, T-student, large sample method. Confidence intervals in linear regression. rec18 audio-video (.mp4) | [T] Chpts. 23.2,23.4, 4.3,24.4 notes2.pdf |

19 | 28.04 9:00-11:00 | Teams | Empirical bootstrap. Application to confidence intervals. rec19 audio-video (.mp4) | [T] Chpts. 18.1,18.2,23.3 slides19 (.pdf), script19 (.R) |

20 | 04.05 16:00-18:00 | Teams | Parametric bootstrap. Hypotheses testing. rec20 audio-video (.mp4) | [T] Chpts. 18.3,25 slides20 (.pdf), script20 (.R) |

21 | 05.05 9:00-11:00 | Teams | One-sample tests of the mean and application to linear regression.rec21 audio-video (.mp4) | [T] Chpts. 26-27, [R] Chpts. 5.1,5.2 slides21 (.pdf), notes2.pdf, script21 (.R) |

22 | 11.05 16:00-18:00 | Teams | Multiple comparisons. Fitting distributions.rec22 audio-video (.mp4) | K-S, slides22 (.pdf), script22 (.R) |

23 | 12.05 9:00-11:00 | Teams | Two-sample tests of the mean, and F-test.rec23 audio-video (.mp4) | [T] Chpts. 28, [R] Chpts. 5.3-5.7 slides23 (.pdf), script23 (.R) |

24 | 18.05 16:00-18:00 | Teams | Testing correlation/independence. Multiple-sample tests of the mean.rec24 audio-video (.mp4) | [R] Chpts. 7, 8 slides24 (.pdf), script24 (.R) |

– | 19.05 9:00-11:00 | Teams | Office hours and project tutoring. |

mds/smd/start.txt · Ultima modifica: 13/04/2022 alle 09:26 (6 settimane fa) da Salvatore Ruggieri