Linked Questions

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1answer
2k views

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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1answer
1k views

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....
0
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1answer
2k views

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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0answers
763 views

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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0answers
490 views

How to interpret the R2 in univariate regression analysis? [duplicate]

How to interpret the R2 in univariate regression analysis ?
5
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0answers
106 views

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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0answers
86 views

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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0answers
10 views

Why are the R-squareds of the subsamples much smaller than the R-squared of the full sample? [duplicate]

I'm hoping to get some intuition on what is happening. My R-squared in the full sample is 10%. When I split my sample into two subsets, my R-squared in each subset is about 1%. I thought the R-...
108
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21answers
33k views

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.
20
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6answers
56k views

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: ...
28
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4answers
53k views

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 ...
23
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3answers
3k views

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?...
14
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5answers
2k views

What does it mean for a linear regression to be statistically significant but has very low r squared?

I understand it to mean that the model is bad at predicting individual data points but has established a firm trend (e.g. y goes up when x goes up).
12
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6answers
36k views

Acceptable r-square value for multiple linear regression model [duplicate]

I'm currently working on my thesis, more specifically I'm analyzing some data collected from researchers about the project's they're working on. In the end, I have performed a multiple linear ...
17
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3answers
32k views

What is the relationship between R-squared and p-value in a regression?

tl;dr - for OLS regression, does a higher R-squared also imply a higher P-value? Specifically for a single explanatory variable (Y = a + bX + e) but would also be interested to know for n multiple ...

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