Statistics DSBA 2020/2021 — различия между версиями

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(не показано 14 промежуточных версии 2 участников)
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! Group!! БПАД191 !! БПАД192 !! БПАД193
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! Group!! БПАД201 !! БПАД202 !! БПАД203
 
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|| Teacher ||colspan="3"| [https://www.hse.ru/org/persons/14276760 Peter Lukianchenko]  
 
|| Teacher ||colspan="3"| [https://www.hse.ru/org/persons/14276760 Peter Lukianchenko]  
 
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|| Assistant || [https://t.me/christopher_dzyura Christopher Dzyura] || TODO || TODO
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|| Assistant || || ||  ||  
 
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= Communication =
 
= Communication =
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= Lecture notes =
 
= Lecture notes =
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'''[https://www.dropbox.com/s/9rfctx62918trey/1%20Lect%20Sept1_d.pdf?dl=0 Lecture 1]''' (01.09.2020). Welcome to Statistics!
 
'''[https://www.dropbox.com/s/9rfctx62918trey/1%20Lect%20Sept1_d.pdf?dl=0 Lecture 1]''' (01.09.2020). Welcome to Statistics!
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'''[https://www.dropbox.com/s/41sobtq08y48947/4%20Lecture%20.pdf?dl=0 Lecture 4]''' (22.09.2020). Joint discrete distribution. Conditional probability. Covariance. Correlation.
 
'''[https://www.dropbox.com/s/41sobtq08y48947/4%20Lecture%20.pdf?dl=0 Lecture 4]''' (22.09.2020). Joint discrete distribution. Conditional probability. Covariance. Correlation.
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'''[https://www.dropbox.com/s/1q0ac1abnpw9tne/5%20Statistics_Lect%20sept%2029_done%20%20-%20%20Compatibility%20Mode.pdf?dl=0 Lecture 5]''' (29.09.2020) Covariance. Correlation. Continuous distribution.
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'''[https://www.dropbox.com/s/usyhdpte0uoakjf/6%20Lecture.pdf?dl=0 Lecture 6]''' (06.10.2020) Continuous distribution.
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'''[https://www.dropbox.com/s/xvcmqibbyw22y7k/Lecture%207.pdf?dl=0 Lecture 7]''' (13.10.2020) Normal distribution. Standard normal distribution. Joint distribution. Uniform distribution.
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'''[https://www.dropbox.com/s/ry3emtfy2f6z4md/8%20Lecture%20.pdf?dl=0 Lecture 8]''' (27.10.2020) Data representation. Exponential, Poisson, and Uniform distributions. Continuity correction.
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'''[https://www.dropbox.com/s/s4gnj126k1qb2wt/9%2010%20Lecture.pdf?dl=0 Lectures 9-10]''' (2-3.11.2020) Law of large numbers. Distribution of a function of random variable. Distribution of sample proportion. Chi-squared distribution.
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'''[https://www.dropbox.com/s/5cvlqt341z83v1v/11%20Lecture.pdf?dl=0 Lecture 11]''' (9.11.2020) Point estimation.
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'''[https://www.dropbox.com/s/ulk6m9zm0raozpd/12%20Lecture%20November%2010.pdf?dl=0 Lecture 12]''' (16.11.2020) Likelihood function.
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'''[https://www.dropbox.com/s/ufo1d3rrdbsd8sl/14%20Lecture.pdf?dl=0 Lecture 14]''' (23.11.2020) Confidence intervals. Part 1
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'''[https://www.dropbox.com/s/rwbqyxnde0y6mcl/15%20Lecture.pdf?dl=0 Lecture 15]''' (30.11.2020) Confidence intervals. Part 2
  
 
= Seminar notes =
 
= Seminar notes =
  
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[https://www.dropbox.com/s/on7mye1f5kpqq0h/sem%201%20Afanasev.pdf?dl=0 Seminar 1]
 
  
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[https://www.dropbox.com/s/9916r2ewhbjcj5b/sem%203%20Afanasev.pdf?dl=0 Seminar 3]
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'''[https://www.dropbox.com/s/on7mye1f5kpqq0h/sem%201%20Afanasev.pdf?dl=0 Seminar 1]'''
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'''[https://www.dropbox.com/s/9916r2ewhbjcj5b/sem%203%20Afanasev.pdf?dl=0 Seminar 3]'''
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'''[https://www.dropbox.com/s/vs5vrc1b2kwkbxd/sem%204%20Afanasev.pdf?dl=0 Seminar 4]'''
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'''[https://www.dropbox.com/s/c8xlztowczpsv2m/sem%205%20Afanasev.pdf?dl=0 Seminar 5]'''
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'''[https://www.dropbox.com/s/j6czzeo8taydnaa/sem%206%20Afanasev.pdf?dl=0 Seminar 6]'''
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'''[https://www.dropbox.com/s/ljwj09tm80fbp4c/sem%207%20Afanasev.pdf?dl=0 Seminar 7]'''
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'''[https://www.dropbox.com/s/oyksqc0naaz03rq/sem%209%20orig.pdf?dl=0 Seminar 9]'''
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'''[https://www.dropbox.com/s/0yv7oskrs4bizjf/sem%2010-11%20Afanasev.pdf?dl=0 Seminar 10-11]'''
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'''[https://www.dropbox.com/s/57efg2oxnfz2228/sem%2012%20Afanasev.pdf?dl=0 Seminar 12]'''
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'''[https://www.dropbox.com/s/3is9ejn0pv985ll/sem%2013%20Afanasev.pdf?dl=0 Seminar 13]'''
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'''[https://www.dropbox.com/s/o8080kj8r879hw0/sem%2014%20Afanasev.pdf?dl=0 Seminar 14]'''
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'''[https://www.dropbox.com/s/dv9s6pp3j7mg3or/sem%2015%20Afanasev.pdf?dl=0 Seminar 15]'''
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'''[https://www.dropbox.com/s/tn52snxcnw95q2i/sem%2016%20Afanasev.pdf?dl=0 Seminar 16]'''
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'''[https://www.dropbox.com/s/vm3t30if7lzqp2x/sem%2017%20Afanasev.pdf?dl=0 Seminar 17]'''
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= Hometask =
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'''[https://docs.google.com/spreadsheets/d/1SnpdGSW5gOMmhbyNOgfIdLn1RFV5Wg-pYgbV73-LWdE/edit?usp=drivesdk Link to Google Sheet with grades]'''
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'''[https://www.dropbox.com/s/zt1kvle0soj68h0/HW1.pdf?dl=0 Hometask 1]''' (Deadline: 18.09.2020) Basics of Probability.
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'''[https://www.dropbox.com/s/i0toc0bae2tk5mm/HW2.pdf?dl=0 Hometask 2]''' (Deadline: 25.09.2020) Probabilities of Complex Events.
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'''[https://www.dropbox.com/s/5o71fadci8gg0dm/HW3.pdf?dl=0 Hometask 3]''' (Deadline: 02.10.2020) Expectation and variance.
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'''[https://www.dropbox.com/s/fcyv79ytugxzcej/HW4.pdf?dl=0 Hometask 4]'''
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'''[https://www.dropbox.com/s/25s9ngvn1my6c0i/Stat2020_HW_5.pdf?dl=0 Hometask 5]'''
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'''[https://www.dropbox.com/s/3901iimtuzy6e01/Stat2020_HW_6.pdf?dl=0 Hometask 6]'''
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'''[https://www.dropbox.com/s/wzw2dqoj0byzgwx/Stat2020_HW_7.pdf?dl=0 Hometask 7]''' (Deadline: 07.12.2020) Method of Moments. Least Squares. Maximum Likelihood.
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Confidence intervals.
  
 
= Grading system =
 
= Grading system =
  
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M1_score = 0.75 * FallExam + 0.25 * M1_Homeworks
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Interim assessment (1 module)
  
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Fall = 0.4 * M1_score + 0.4 * WinterMock + 0.2*FallHomeWork
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0.7 * FallMock (October Midterm) + 0.3 * First module Home assignments
  
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Spring = 0.2 * SpringMock + 0.15 * Final exam + 0.5 * UoL + 0.025 * SpringHomework + 0.15 * SpringHomeWork
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Interim assessment (4 module)
  
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Final = 0.4 * Fall + 0.6 * Spring
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0.17 * 2nd-4th module Home assignments + 0.09 * FinalExam (June Exam) + 0.16 * Interim assessment (1 module) + 0.12 * SpringMock (Spring Midterm) + 0.3 * University of London exams (May Exam) + 0.16 * WinterExam (December Exam)
  
 
All marks are out of 100 points.
 
All marks are out of 100 points.

Текущая версия на 18:52, 25 октября 2021

About

This page contains information about Statistics course at DSBA.

Actual syllabus can be found here.

Teachers and assistants

Group БПАД201 БПАД202 БПАД203
Teacher Peter Lukianchenko
Assistant


Communication

We use Telegram messenger to share files and Zoom meetings links.

Link to course channel: click

Lecture notes

Lecture 1 (01.09.2020). Welcome to Statistics!

Lecture 2 (08.09.2020). Axioms of probability. Basics of combinatorics. Geometric probability.

Lecture 3 (15.09.2020). Random variable. Discrete pdf. Expectation and variance. Bernoulli distribution. Bayes rule.

Lecture 4 (22.09.2020). Joint discrete distribution. Conditional probability. Covariance. Correlation.

Lecture 5 (29.09.2020) Covariance. Correlation. Continuous distribution.

Lecture 6 (06.10.2020) Continuous distribution.

Lecture 7 (13.10.2020) Normal distribution. Standard normal distribution. Joint distribution. Uniform distribution.

Lecture 8 (27.10.2020) Data representation. Exponential, Poisson, and Uniform distributions. Continuity correction.

Lectures 9-10 (2-3.11.2020) Law of large numbers. Distribution of a function of random variable. Distribution of sample proportion. Chi-squared distribution.

Lecture 11 (9.11.2020) Point estimation.

Lecture 12 (16.11.2020) Likelihood function.

Lecture 14 (23.11.2020) Confidence intervals. Part 1

Lecture 15 (30.11.2020) Confidence intervals. Part 2

Seminar notes

Seminar 1

Seminar 3

Seminar 4

Seminar 5

Seminar 6

Seminar 7

Seminar 9

Seminar 10-11

Seminar 12

Seminar 13

Seminar 14

Seminar 15

Seminar 16

Seminar 17

Hometask

Link to Google Sheet with grades

Hometask 1 (Deadline: 18.09.2020) Basics of Probability.

Hometask 2 (Deadline: 25.09.2020) Probabilities of Complex Events.

Hometask 3 (Deadline: 02.10.2020) Expectation and variance.

Hometask 4

Hometask 5

Hometask 6

Hometask 7 (Deadline: 07.12.2020) Method of Moments. Least Squares. Maximum Likelihood. Confidence intervals.

Grading system

Interim assessment (1 module)

0.7 * FallMock (October Midterm) + 0.3 * First module Home assignments

Interim assessment (4 module)

0.17 * 2nd-4th module Home assignments + 0.09 * FinalExam (June Exam) + 0.16 * Interim assessment (1 module) + 0.12 * SpringMock (Spring Midterm) + 0.3 * University of London exams (May Exam) + 0.16 * WinterExam (December Exam)

All marks are out of 100 points.

Rules

  • Homework submitted after the general deadline will not be accepted.
  • The common mistakes made in the homework will be discussed during the seminars.
  • Any fact of cheating or breach of academic integrity will result in receiving a "0" (zero) for this work.
Источник — «http://wiki.cs.hse.ru/index.php?title=Statistics_DSBA_2020/2021&oldid=60376»