Statistics DSBA 2021/2022 — различия между версиями

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(Новая страница: «= About = This page contains information about Statistics course at DSBA. Actual syllabus can be found [https://www.dropbox.com/s/1rxg7910zxakznv/Syllabus%20for…»)
 
(Lecture notes)
 
(не показаны 3 промежуточные версии этого же участника)
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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!
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'''[https://www.dropbox.com/s/9rfctx62918trey/1%20Lect%20Sept1_d.pdf?dl=0 Lecture 1]''' (01.09.2021). Welcome to Statistics!
  
'''[https://www.dropbox.com/s/ttiuqmi7nu9e641/Lecture%202.pdf?dl=0 Lecture 2]''' (08.09.2020). Axioms of probability. Basics of combinatorics. Geometric probability.
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'''[https://www.dropbox.com/s/ttiuqmi7nu9e641/Lecture%202.pdf?dl=0 Lecture 2]''' (08.09.2021). Axioms of probability. Basics of combinatorics. Geometric probability.
  
'''[https://www.dropbox.com/s/26t4yx47iijxmq9/3.%20Stat_3%20%28ppt%2097-2003%29_d.pdf?dl=0 Lecture 3]''' (15.09.2020). Random variable. Discrete pdf. Expectation and variance. Bernoulli distribution. Bayes rule.
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'''[https://www.dropbox.com/s/26t4yx47iijxmq9/3.%20Stat_3%20%28ppt%2097-2003%29_d.pdf?dl=0 Lecture 3]''' (15.09.2021). Random variable. Discrete pdf. Expectation and variance. Bernoulli distribution. Bayes rule.
  
'''[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/41sobtq08y48947/4%20Lecture%20.pdf?dl=0 Lecture 4]''' (22.09.2021). Joint discrete distribution. Conditional probability. Covariance. Correlation.
  
'''[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/1q0ac1abnpw9tne/5%20Statistics_Lect%20sept%2029_done%20%20-%20%20Compatibility%20Mode.pdf?dl=0 Lecture 5]''' (29.09.2021) Covariance. Correlation. Continuous distribution.
  
'''[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/usyhdpte0uoakjf/6%20Lecture.pdf?dl=0 Lecture 6]''' (06.10.2021) Continuous distribution.
  
'''[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/xvcmqibbyw22y7k/Lecture%207.pdf?dl=0 Lecture 7]''' (13.10.2021) Normal distribution. Standard normal distribution. Joint distribution. Uniform distribution.
  
'''[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/ry3emtfy2f6z4md/8%20Lecture%20.pdf?dl=0 Lecture 8]''' (27.10.2021) Data representation. Exponential, Poisson, and Uniform distributions. Continuity correction.
  
'''[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/s4gnj126k1qb2wt/9%2010%20Lecture.pdf?dl=0 Lectures 9-10]''' (2-3.11.2021) 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
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= Seminar notes =
 
= Seminar notes =
 
 
'''[https://www.dropbox.com/s/on7mye1f5kpqq0h/sem%201%20Afanasev.pdf?dl=0 Seminar 1]'''
 
 
'''[https://www.dropbox.com/s/9916r2ewhbjcj5b/sem%203%20Afanasev.pdf?dl=0 Seminar 3]'''
 
 
'''[https://www.dropbox.com/s/vs5vrc1b2kwkbxd/sem%204%20Afanasev.pdf?dl=0 Seminar 4]'''
 
 
'''[https://www.dropbox.com/s/c8xlztowczpsv2m/sem%205%20Afanasev.pdf?dl=0 Seminar 5]'''
 
 
'''[https://www.dropbox.com/s/j6czzeo8taydnaa/sem%206%20Afanasev.pdf?dl=0 Seminar 6]'''
 
 
'''[https://www.dropbox.com/s/ljwj09tm80fbp4c/sem%207%20Afanasev.pdf?dl=0 Seminar 7]'''
 
 
'''[https://www.dropbox.com/s/oyksqc0naaz03rq/sem%209%20orig.pdf?dl=0 Seminar 9]'''
 
 
'''[https://www.dropbox.com/s/0yv7oskrs4bizjf/sem%2010-11%20Afanasev.pdf?dl=0 Seminar 10-11]'''
 
 
'''[https://www.dropbox.com/s/57efg2oxnfz2228/sem%2012%20Afanasev.pdf?dl=0 Seminar 12]'''
 
 
'''[https://www.dropbox.com/s/3is9ejn0pv985ll/sem%2013%20Afanasev.pdf?dl=0 Seminar 13]'''
 
 
'''[https://www.dropbox.com/s/o8080kj8r879hw0/sem%2014%20Afanasev.pdf?dl=0 Seminar 14]'''
 
 
'''[https://www.dropbox.com/s/dv9s6pp3j7mg3or/sem%2015%20Afanasev.pdf?dl=0 Seminar 15]'''
 
 
'''[https://www.dropbox.com/s/tn52snxcnw95q2i/sem%2016%20Afanasev.pdf?dl=0 Seminar 16]'''
 
 
'''[https://www.dropbox.com/s/vm3t30if7lzqp2x/sem%2017%20Afanasev.pdf?dl=0 Seminar 17]'''
 
  
 
= Hometask =
 
= Hometask =
 
'''[https://docs.google.com/spreadsheets/d/1SnpdGSW5gOMmhbyNOgfIdLn1RFV5Wg-pYgbV73-LWdE/edit?usp=drivesdk Link to Google Sheet with grades]'''
 
 
'''[https://www.dropbox.com/s/zt1kvle0soj68h0/HW1.pdf?dl=0 Hometask 1]''' (Deadline: 18.09.2020) Basics of Probability.
 
 
'''[https://www.dropbox.com/s/i0toc0bae2tk5mm/HW2.pdf?dl=0 Hometask 2]''' (Deadline: 25.09.2020) Probabilities of Complex Events.
 
 
'''[https://www.dropbox.com/s/5o71fadci8gg0dm/HW3.pdf?dl=0 Hometask 3]''' (Deadline: 02.10.2020) Expectation and variance.
 
 
'''[https://www.dropbox.com/s/fcyv79ytugxzcej/HW4.pdf?dl=0 Hometask 4]'''
 
 
'''[https://www.dropbox.com/s/25s9ngvn1my6c0i/Stat2020_HW_5.pdf?dl=0 Hometask 5]'''
 
 
'''[https://www.dropbox.com/s/3901iimtuzy6e01/Stat2020_HW_6.pdf?dl=0 Hometask 6]'''
 
 
'''[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.
 
Confidence intervals.
 
  
 
= Grading system =
 
= Grading system =

Текущая версия на 18:55, 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 БПАД204
Teacher Peter Lukianchenko
Assistant Ivanov Anton Varvara Erinova Egor Nikitin Kseniia Shilova

If you feel like something is missing from this page, please feel free to ping Axyniia.

Communication

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

Link to course channel: click

Lecture notes

Lecture 1 (01.09.2021). Welcome to Statistics!

Lecture 2 (08.09.2021). Axioms of probability. Basics of combinatorics. Geometric probability.

Lecture 3 (15.09.2021). Random variable. Discrete pdf. Expectation and variance. Bernoulli distribution. Bayes rule.

Lecture 4 (22.09.2021). Joint discrete distribution. Conditional probability. Covariance. Correlation.

Lecture 5 (29.09.2021) Covariance. Correlation. Continuous distribution.

Lecture 6 (06.10.2021) Continuous distribution.

Lecture 7 (13.10.2021) Normal distribution. Standard normal distribution. Joint distribution. Uniform distribution.

Lecture 8 (27.10.2021) Data representation. Exponential, Poisson, and Uniform distributions. Continuity correction.

Lectures 9-10 (2-3.11.2021) Law of large numbers. Distribution of a function of random variable. Distribution of sample proportion. Chi-squared distribution.

Seminar notes

Hometask

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.