mds:smd:start
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| mds:smd:start [22/05/2019 alle 06:21 (7 anni fa)] – [Class calendar] Salvatore Ruggieri | mds:smd:start [16/01/2026 alle 20:00 (8 mesi fa)] (versione attuale) – eliminata Salvatore Ruggieri | ||
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| - | ====== Statistical Methods for Data Science A.Y. 2018/19 ====== | ||
| - | |||
| - | =====Instructor===== | ||
| - | |||
| - | * **Salvatore Ruggieri** | ||
| - | * Università di Pisa | ||
| - | * [[http:// | ||
| - | * [[ruggieri@di.unipi.it]] | ||
| - | * **Office hours** | ||
| - | * Tuesday h 14:00 - 17:00, Department of Computer Science, room 321/ | ||
| - | |||
| - | < | ||
| - | <p style=" | ||
| - | </ | ||
| - | |||
| - | =====Classes===== | ||
| - | |||
| - | ^ Day of Week ^ Hour ^ Room ^ | ||
| - | | Monday | 14:00 - 16:00 | Fib-N1 | ||
| - | | Tuesday | 9:00 - 11:00 | Fib-A1 | ||
| - | |||
| - | |||
| - | =====Pre-requisites===== | ||
| - | |||
| - | 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__. | ||
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| - | Extra-lessons refreshing such notions may be planned in the first part of the course. | ||
| - | |||
| - | |||
| - | =====Text Books===== | ||
| - | |||
| - | 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. | ||
| - | |||
| - | =====Software===== | ||
| - | |||
| - | * [[https:// | ||
| - | * [[https:// | ||
| - | |||
| - | =====Preliminary program and calendar===== | ||
| - | |||
| - | * [[https:// | ||
| - | * [[https:// | ||
| - | |||
| - | |||
| - | =====Project===== | ||
| - | |||
| - | * Project can be done in groups of at most 3 students. | ||
| - | * Project must be completed by end of July, including oral discussion (on project and all topics of the course). | ||
| - | * Project replace the written exam but **students have to [[https:// | ||
| - | * {{ : | ||
| - | * [[https:// | ||
| - | =====Written exam===== | ||
| - | |||
| - | __//There are no mid-terms// | ||
| - | Registration to exams is mandatory: [[https:// | ||
| - | |||
| - | ^ Date ^ Hour ^ Room ^ | ||
| - | | 18/ | ||
| - | | 2/ | ||
| - | | 24/ | ||
| - | =====Class calendar===== | ||
| - | |||
| - | ^ ^ Date ^ Room ^ Topic ^ Learning material ^ | ||
| - | |1| 18.02 14:00-16:00 | N1 | Introduction. Probability and independence. | **[T]** Chpts. 1-3 | | ||
| - | |2| 19.02 9:00-11:00 | A1 | R basics. | ||
| - | |3| 26.02 9:00-11:00 | A1 | Discrete random variables. | ||
| - | |4| 4.03 14:00-16:00 | N1 | Continuous random variables. Simulation. | ||
| - | |5| 5.03 9:00-11:00 | A1 | Expectation and variance. R data access. | ||
| - | |6| 12.03 9:00-11:00 | A1 | Recalls: derivatives and integrals. | ||
| - | |7| 13.03 11:00-13:00 | I-Lab | Power laws and Zipf laws. | [[https:// | ||
| - | |8| 18.03 14:00-16:00 | N1 | Zipf laws. Project presentation. | ||
| - | |9| 19.03 9:00-11:00 | A1 | R programming. | ||
| - | |10| 20.03 11:00-13:00 | I-Lab | Computations with random variables. Joint distributions. | ||
| - | |11| 25.03 14:00-16:00 | N1 | Covariance. Sum of random variables. | ||
| - | |12| 26.03 9:00-11:00 | A1 | Law of large numbers. The central limit theorem. | ||
| - | |13| 8.04 14:00-16:00 | N1 | Graphical summaries. | ||
| - | |14| 9.04 9:00-11:00 | A1 | Numerical summaries. Data preprocessing in R. Q&A on the project. | ||
| - | |15| 15.04 14:00-16:00 | N1 | Unbiased estimators. Efficiency and MSE | **[T]** Chpts. 17.1-17.3, 19, 20 {{ : | ||
| - | |16| 16.04 9:00-11:00 | A1 | Maximum likelihood. Fisher information. | ||
| - | |17| 29.04 14:00-16:00 | N1 | Linear, polynomial, and non-linear regressions and least squares. | ||
| - | |18| 30.04 9:00-11:00 | A1 | Confidence Intervals: Gaussian, T-student, large sample method. | ||
| - | |19| 7.05 9:00-11:00 | A1 | Empirical bootstrap. Application to confidence intervals. | ||
| - | |20| 8.05 11:00-13:00 | I-Lab | Parametric bootstrap. Hypotheses testing. | ||
| - | |21| 20.05 14:00-16:00 | N1 | One-sample t-test and application to linear regression. | ||
| - | |22| **22.05 11: | ||
| - | | | < | ||
| - | |23| 28.05 9:00-11:00 | A1 | ... | ... | | ||
| - | |24| **29.05 11: | ||
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| - | =====Previous years===== | ||
| - | |||
| - | * [[mds: | ||
| - | * [[mds: | ||
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mds/smd/start.1558506064.txt.gz · Ultima modifica: da Salvatore Ruggieri