Statistics DSBA 2019/2020 — различия между версиями

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Link to course channel: [https://t.me/stathard]
 
Link to course channel: [https://t.me/stathard]
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Questions about homework assignments can be addressed to Tagir (tg @Kuskarov).
  
 
= Lecture notes =
 
= Lecture notes =

Версия 21:56, 4 мая 2020

About

This page contains information about Statistics course at DSBA.

Actual syllabus can be found here.

Teachers and assistants

Group БПАД181 БПАД182
Teacher Peter Lukianchenko
Assistant Anastasia Tabisheva Igor Fedorov

Office hours

Teacher/Assistant Monday Tuesday Wednesday Thursday Friday Saturday
1
Peter Lukianchenko
2
Anastasia Tabisheva
3
Igor Fedorov
4
Tagir Kuskarov

Communication

We use Telegram messenger to share files.

Link to course channel: [1]

Questions about homework assignments can be addressed to Tagir (tg @Kuskarov).

Lecture notes

Lecture 1 (4.09.2019). Welcome to Statistics!

Lecture 2 (11.09.2019). Axioms of probability. Basics of combinatorics.

Lecture 3 (18.09.2019). Random variable. Discrete pdf. Expectation and variance. Bernoulli distribution. Bayes rule.

Lecture 4 (25.09.2019). Joint discrete distribution. Conditional probability. Covariance. Correlation.

Lecture 5 (2.10.2019). Continuous distribution. Standard normal distribution. Exponential distribution. Uniform distribution

Lecture 6 (9.10.2019). Normal distribution. Standard normal distribution. Joint distribution. Uniform distribution

Lecture 7 (16.10.2019). Normal distribution. Standard normal distribution. Joint distribution. Uniform distribution.

Lecture 8 (06.11.2019). Data representation. Exponential, Poisson, and Uniform distributions. Continuity correction.

Lecture 9 (13.11.2019). Law of large numbers. Distribution of a function of random variable. Distribution of sample proportion. Chi-squared distribution.

Lecture 10 (18.11.2019). Student distribution. Chi-squared distribution.

Lecture 11 (20.11.2019). Sampling. Sample mean. Fisher lemma. Point estimation. F-distribution.

Lecture 12 (27.11.2019). Interval estimation. Confidence interval.

Lecture 13 (4.12.2019). Confidence interval.

Too lazy to post links anymore... Look here to find other lectures.

Grading system

Fall = 0.3 * FallMock + 0.6 * WinterExam + 0.05 * FallHomework + 0.05 * FallQuizzes

Spring = 0.15 * SpringMock + 0.4 * Final exam + 0.4 * UoL + 0.025 * SpringHomework + 0.025 * SpringQuizes

Final = 0.4 * Fall + 0.6 * Spring

All marks are out of 100 points.

Examination types

  • Home assignments and Quizzes
  • FallMock (October Midterm)
  • WinterExam (December Exam)
  • SpringMock (spring)
  • University of London exams (May Exam)
  • FinalExam (June Exam).

Results

Homeworks and Quizes

Fall grades: Link

Spring grades: Link

Fall Exam

Results of Fall Exam in group 181: Link

Results of Fall Exam in group 182: Link

Free response part solutions are available here.

Homework assignments

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.

Problems

Homework 2 until 10:30, 25.09.2019

Homework 3 until 10:30, 9.10.2019

Homework 4 until 10:30, 16.10.2019

Homework 5 until 10:30, 13.11.2019

Homework 6 until 12:00, 19.11.2019

Homework 7 until 15:00, 29.11.2019

Homework 8 until 12:00, 13.12.2019

Other HWs can be found in the telegram channel or here.