Stats4Everyone

Вывод и объяснение формулы для ожидаемых частот в критерии независимости хи-квадрат

Почему мы используем разные распределения для разных доверительных интервалов? z, t, хи-квадрат, F?

Найти уникальный список данных в Excel и подсчитать количество вхождений, используя =unique(...) ...

Stata - В чём разница между функциями egen и generate? Ответ: как они обрабатывают пропущенные зн...

Простой пример использования индекса и сопоставления в Excel (с простым примером данных), фильтра...

Простой способ фильтрации данных в Excel (с простым примером данных) с помощью =filter(...)

Как использовать уравнение ФИЛЬТР в Excel (с примером реальных данных)

Stata - How to open and save a .do file and how to import .csv and .dta data

Stata - How to generate new variables, use egen to add variables, find a variable mean, and 2x2table

Nelder & Wedderburn 1972 - GLM - Sufficient Statistics - Equation 11

Nelder & Wedderburn 1972- GLM- Sufficient Statistics - Show the sum of z*x are sufficient statistics

Nelder & Wedderburn 1972 - GLM - Sufficient Statistics - Equation 10

Nelder & Wedderburn 1972 - Poisson Example - Step3: Find the MLE using iterative WLS in R

Nelder & Wedderburn 1972 - Poisson Example - Step2: Identify w and y in the MLE procedure

Nelder & Wedderburn 1972 - Poisson Example - Step1: show Poisson is from the Exponential Family

Examples finding expected value of a constant: E(a) = a, and expected value of X: E(X)

Proof for the variance of a difference of random variables: Var(X-Y) = Var(X)+Var(Y)-2Cov(X,Y)

Proof for the variance of a sum of random variables: Var(X+Y)=Var(X)+Var(Y)+2Cov(X,Y)

Proof that variance of a constant times X is the constant squared times var of X: Var(aX)=a^2 Var(X)

Proof that the variance of a constant is zero: Var(a) = 0

Proof that expected value of a product is the product of expected values: E(XY) = E(X)E(Y)

Proof that expected value of sum of random variables is the sum of expected values: E(X+Y)=E(X)+E(Y)

Proof that expected value of constant times X = constant times expected value of X: E(aX) = aE(X)

Proof that expected value of a constant is the constant: E(a) = a

Nelder & Wedderburn 1972 - Bernoulli Example - Step3: Find the MLE using iterative WLS in R

Nelder & Wedderburn 1972 - Bernoulli Example - Step2: Identify w and y in the MLE procedure

Nelder & Wedderburn 1972 - Bernoulli Example - Step1: show Bernoulli is from the Exponential Family

Nelder & Wedderburn 1972 - Why don't they have n independent z in their Likelihood?

Nelder & Wedderburn 1972 - GLM - MLE - Equivalence to Weighted LS - Normal Distribution Example

Nelder & Wedderburn 1972 - GLM - MLE - Equivalence to Weighted Least Squares - Part 2