7k views

If so many people use set.seed(123) doesn't that affect randomness of world's reporting? [duplicate]

It seems like everyone just uses set.seed(123) or set.seed(1234) when they are doing random sampling. If so many people use ...
15k views

Choosing a value for random_state argument in scikit-learn linear regression [duplicate]

A value of 324 is provided without explanation in a linear regression tutorial that I'm following. I checked to see if this was the number of samples, but they did not match. Edit: My apologies for ...
52 views

Why a lot of people use random.seed() at the beginning of their python code [duplicate]

A lot of people use random.seed() at the beginning of their python code in training a machine learning model. As I understand they want to control the randomness therefore they can compare different ...
4k views

Why does collecting data until finding a significant result increase Type I error rate?

I was wondering exactly why collecting data until a significant result (e.g., $p \lt .05$) is obtained (i.e., p-hacking) increases the Type I error rate? I would also highly appreciate an ...
8k views

Choosing the “Correct” Seed for Reproducible Research/Results

I have created this post to spark a discussion around an idea I had regarding the choice of the seed number used to replicate the results of a statistical model. Here is some background on how I came ...
2k views

Why does changing random seeds alter results?

I'm running some SVMs for a seminar and a friend of mine noted I should set a seed so my results don't change everytime I run the code. I was wondering why is that the case. If a different seed can ...
1k views

Is there such a thing as a “good/bad” seed in pseudo-random number generation?

Well, I don't really have much to add to the title. I tend not to use seeds in preudo-random number generation, but they are handy when an initial research project that includes simulations expands to ...
908 views

Performance of Ridge and Lasso Regression depend on set.seed?

I try to do a ridge and lasso regression for out of sample predictions. The optimal lambda is chosed via cross validation. I run my results for different seeds in R. And depending on the seed i get a ...
287 views

Why do we do hypothesis testing on estimates of linear regression?

I was reading about linear regression and what I understood is that once we minimize OLS equation we get the beta parameters. Its just like solving a normal equation to get the unknowns. Then why do ...