Probability and Statistics (DSBA)
This page contains information about Statistics course at DSBA.
Actual syllabus can be found here.
Teachers and assistants
|Assistant||Maria Alekseeva||Matvey Ryumin||Kirill Khodakovskiy||Anastasia Chernysheva|
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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.
2022/2023 2nd module
0.25 * Fall Home assignments + 0.25 * Fall midterm + 0.5 * Winter exam
2022/2023 4th module
Module2_score*0,3+ HA (m3-m4)*0,3+ Spring Midterm*0,25+Final Exam*0,15
- 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.