Statistics4MR-2022-23 — различия между версиями
Материал из Wiki - Факультет компьютерных наук
(Добавлена ссылка на семинары) |
Bdemeshev (обсуждение | вклад) |
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Final grade = 0.5 * Fall grade + 0.2 HA + 0.3 * Final exam | Final grade = 0.5 * Fall grade + 0.2 HA + 0.3 * Final exam | ||
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+ | [https://docs.google.com/spreadsheets/d/e/2PACX-1vQJv_9-5FgPZOVN8Kr3iCYqWVuHsOFro12SRdsQf90w214IJpGAETqOG6_EUwVux6OgCae0kgzmldQ2/pub?output=xlsx Actual grades] | ||
== Log-book == | == Log-book == |
Версия 14:45, 9 октября 2022
Содержание
Plan
Нажми "развернуть", чтобы просмотреть содержимое - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 🡣
Grades
UoL grade = 0.7 * UoL exam + 0.3 * UoL coursework
Internal grades:
Fall grade = 0.4 * HA + 0.6 December Exam
Final grade = 0.5 * Fall grade + 0.2 HA + 0.3 * Final exam
Log-book
Week 1
Naive bootstrap, t-statistic bootstrap
Sources of wisdom:
Efron, Leisurely Look at bootstrap, jackknife and cv
Tim Hesterberg, What Teachers Should Know about the Bootstrap?
Week 2
Variance estimation: jackknife, bootstrap. Bootstrap in bootstrap.
Week 3
Examples of bootstrap failures, problem solving