Linked Questions
126 questions linked to/from Is $R^2$ useful or dangerous?
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When to not use R squared [duplicate]
I recently graduated graduate school and am looking for a proof on R squared. Specifically when to not use it. I really remember a professor impressing upon me multiple times not to report R squared ...
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The larger $R^2$ the better? [duplicate]
I want to show that the variable $X$ is significant.
In model 1, I use financial statements variables, other macroeconomic variables and $X$.
Here, $X$ is siginificant at a 10% level and $R^2$ is 0....
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What is a good R^2 value? [duplicate]
I understand the answer to this question is that it entirely depends on the data set.
However, this does not help people understand if their model is suitable or whether they should explore other ...
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What do r (Pearson correlation coefficient) and R^2 stand for? [duplicate]
As far as I understood, R squared explains how much the variation in Y is explained by its linear association with X. And it's used as an indicator for goodness of fit of a linear model.
Then when ...
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Mathematically, what are the drawbacks of R-squared in evaluation a regression model? [duplicate]
I kept seeing articles about the drawbacks of R-squared (and that's why we need to have adjusted R-squared).
One drawback is that: "Every time you add a predictor to a model, the R-squared increases,...
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How to interpret the R2 in univariate regression analysis? [duplicate]
How to interpret the R2 in univariate regression analysis ?
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Can $R^2$ be applied to non-linear least square regression? [duplicate]
$R^2$ is usually used as a measure to determine a goodness of a fit. It appears to be used often times for linear least square fits, linear regression.
There's another measure which is RSS (residual ...
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Is $R^2$ useless? [duplicate]
I stumbled on a discussion regarding the usefulness of $R^2$ as a metric. Where $R^2$ is defined as:
$$ \frac{\sum (\hat{y} - \bar{\hat{y}})^2 } {\sum(y - \bar{y})^2 }.$$
The criticism is backed by ...
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R2 value lower on all subsets of data than entire dataset [duplicate]
I have a little bit of a conundrum that I am trying to work through.
I'm fitting a time series model with a rolling window of around ~300 samples and then predicting the next sample that comes up.
I ...
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When conducting multiple regression, when should you center your predictor variables & when should you standardize them?
In some literature, I have read that a regression with multiple explanatory variables, if in different units, needed to be standardized. (Standardizing consists in subtracting the mean and dividing ...
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What's a real-world example of "overfitting"?
I kind of understand what "overfitting" means, but I need help as to how to come up with a real-world example that applies to overfitting.
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What are the worst (commonly adopted) ideas/principles in statistics?
In my statistical teaching, I encounter some stubborn ideas/principles relating to statistics that have become popularised, yet seem to me to be misleading, or in some cases utterly without merit. I ...
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Simple linear regression output interpretation
I have run a simple linear regression of the natural log of 2 variables to determine if they correlate. My output is this:
...
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Pseudo R squared formula for GLMs
I found a formula for pseudo $R^2$ in the book Extending the Linear Model with R, Julian J. Faraway (p. 59).
$$1-\frac{\text{ResidualDeviance}}{\text{NullDeviance}}$$.
Is this a common formula for ...
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Is a high $R^2$ ever useless?
In stats we're doing linear regressions, the very beginnings of them. In general, we know that the higher the $R^2$ the better, but is there ever a scenario where a high $R^2$ would be a useless model?...
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