Panda-metrics-2024-25
Содержание
What-about
Course whitepaper
Course goals
侍には目標がなく道しかない [Samurai niwa mokuhyō ga naku michi shikanai]
A samurai has no goal, only a path.
Telegram channel, Telegram chat
Lecture and class hand-made (with love) video recordings + official videos ya-folded
Grading
Semester-1 grade = 0.2 HA-1 + 0.4 Exam-Alpha + 0.4 Exam-Beta.
Semester-2 grade = 0.2 HA-2 + 0.4 Exam-Gamma + 0.4 Exam-Delta.
Final course grade = 0.5 Semester-1 grade + 0.5 Semester-2 grade
Home assignments
Home assignments have equal weights. You have 4 honey weeks for the entire course.
Exams
Samurai diary
2024-09-02, lecture 1: Derivation of beta hat in the cases of a very simple regression and multiple regression.
2024-09-09, lecture 2: Geometry of regression. Fitted vector is the projection of y-vector onto the Span of regressors. Hat-matrix: definition, simple properties. SST, SSE, SSR: definition, Pythagorean theorem: SST = SSE + SSR.
2024-09-16, lecture 3: Conditional expected value, conditional variance. Statistical assumptions for simple regression. Expected value of beta hat for simple regression. Statistical assumptions for multiple regression. Expected value of beta hat for multiple regression. Variance of beta hat for multiple regression.
Classes
2024-09-06, class 1: 1.1, 1.2 from MPro
2024-09-13, class 2: 3.2, 3.10, 3.7 from MPro
Sources of Wisdom
CausML: Causality in ML book with python and R code
MPro-en: Problem set for classes (translation in progress)
MPro-ru: Problem set for classes (in Russian)
