Statistics DSBA 2021/2022
This page contains information about Statistics course at DSBA.
Actual syllabus can be found here.
Teachers and assistants
|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.
We use Telegram messenger to share files and Zoom meetings links.
Link to course channel: click
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.
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.
- 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.