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-1 votes

What model for continuous data with excess zeros?

I would formulate a continuous "underlying" model that is scientifically justifiable and then "censor" it to allow certain degree of discreteness to describe the data collected.
Zack Fisher's user avatar
0 votes

Help clarify the implication of normality in an Ordinary Least Square (OLS) Regression

The original claim probably implied or mentioned elsewhere that the conditional distributions have constant variance. However, without that assumption, the claim is false, as the below simulation ...
Dave's user avatar
  • 64.9k
4 votes

How to determine relative contribution of explanatory variables in a linear regression

If $\mathcal{M}_1$ is your full model and you want to know the contribution of $X_1$ for example, then you fit another model $\mathcal{M}_2$ that includes everything but $X_1$. You can then compute a ...
Frans Rodenburg's user avatar
0 votes

ADALINE simple implementation with 2 features bug

Two mistakes: ADALINE needs the outputs to be encoded as $\pm 1$, not as $\{0, 1\}$, if you want your class boundary equation to be the way you stated it; and, consequently the threshold for ...
Igor F.'s user avatar
  • 9,418
1 vote

Didactic example of mean-variance dependency in linear models

I like the idea of showing the consequences of not respecting the mean-variance relationship. However, I would say that there are more issues than just that if you attempt to model counts with an ...
Frans Rodenburg's user avatar
0 votes

on a linear regression analysis, the determination coefficient is 0.99, but the residuals are not distributed normally. How do I interpret this?

Since this is a homework problem, I will beat around the bush a bit and will not be giving a final determination about how to interpret your $R^2$ score. Hopefully, however, you can use what I write ...
Dave's user avatar
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