|
You are here |
blog.foletta.net | ||
| | | | |
post8000.svmiller.com
|
|
| | | | | ||
| | | | |
svmiller.com
|
|
| | | | | Linear model diagnostics for linearity and heteroskedasticity can induce you to make different design choices, which have implications for statistical significance. The example here is the effect o... | |
| | | | |
freerangestats.info
|
|
| | | | | Stepwise variable selection is bad and dangerous, and you shouldn't do it. It increases false positives. It drops variables that should be in the model. It gives biased estimates for regression coefficients. The problems are worse for smaller samples; higher correlation between the X variables; and models with weaker explanatory power for the y (i.e. lower R-squared). | |
| | | | |
www.jeremymorgan.com
|
|
| | | Want to learn about PyTorch? Of course you do. This tutorial covers PyTorch basics, creating a simple neural network, and applying it to classify handwritten digits. | ||