What is a fixed effect fixed with respect to, or fixed by? I find myself wondering about this in relation to a paper I read yesterday. They describe a linear model like: \begin{align} y_{ij} &= \beta_0 + \beta_1 X_{ij} + u_{0i} + u_{1i} X_{ij} + e_
1. What qualities of a situation make statistics appropriate or useful? 2. Basic statistics makes a lot of assumptions that have to be wrong (charitably: not exactly right), so how does it manage to work much of the time anyway? Things like: Stationarity, possibly independence. 3. How does the question
I recently tried to use gsDesign to calculate sample sizes for a language model question-answering experiment. Unfortunately, it didn't seem to work. I was calculating the size for a fixed-sample design with and without the package. THe package was giving me a sample size more than twice as
1. What does independence mean? Is it an assumption you have to verify? What changes when it is violated? 2. Stationarity. As I undertand it, roughly it means the situation you are statistics-ing doesn't change (when relaxed: too much, too quickly). Basic statistics pretends you have this property.
"your most impressive accomplishment" i've seen this prompt three or four times. feels like dozens. what's an accomplishment? stupid question. i often think of something, and inevitably the thing feels like: 1. #iamverysmart. not self-defeating like the subreddit, but academic, and revealing for what