# Questions tagged [r-squared]

The coefficient of determination, usually symbolized by $R^2$, is the proportion of the total response variance explained by a regression model. Can also be used for various pseudo R-squared proposed, for instance for logistic regression (and other models.)

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### Given a predictor $x$. under what circumstance would you have high $R^2$ but low $\beta$

Assume I have a time series $y$ and a predictor $x$. Let's say they are both centered at zero. $$R^2 = 1 - \frac{ \sum (y_i - x_i)^2 }{\sum y_i^2}$$ Now I run a new regression $y \sim \beta x$, in an ...
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### What can cause a negative R-Squared (between) with Fixed Effects estimation [closed]

I'm analyzing the S&P500 companies for my master thesis about employee happiness and entrepreneurial orientation. I have a panel dataset (2016-2020) with 208 complete entries. My problem is that ...
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### Is it appropriate to use R² on filtering data?

At work, someone has built a dashboard to identify individuals likely to have higher value of the output variable. The approach involves fitting a OLS and measuring the R² value. They attempt to ...
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### Unacceptable results for adj R2

I have a dataset with 19 features. When I ran it with the Lasso algorithm. R2 for test and train was 0.69. But the value of adj r2 for test is 1.28 (above 1), and for train the value is 0.28. What is ...
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### Higher order moments to evaluate strength of linear relationship between variables

Let $X_1,\dots,X_n$ be real random variables such that $\alpha_1X_1+\dots+\alpha_nX_n=0$ for some unknown $\alpha_1,\dots,\alpha_n$. If $n=2$, one can study the strength of linear relationship by ...
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### How to improve a model with little dataset? [duplicate]

I have a dataset that has 20 features and 65 samples. I did data scaling. I also did feature selection in different ways. But this is the result. ...
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### Adjusted R^2 or Lack of Fit

This might be a basic question, but I'll still ask, as I haven't found any proper conclusions from the forums. I'm fitting my data using the Response Surface methodology. So, ideally, the relation ...
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### R squared in logistic regression adjusted for number of predictors

For OLS we have an adjusted R squared which adjusts for the number of predictors included in the model. For logistic regression there are some R squared analogues (Tjur’s R squared, McFadden’s R ...
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### Sum of squares of xy bigger than sum of squares for x - how can that be?

I followed this tutorial to visualize R squared. First they define the formula to calculate sums of squares: Then they apply the formula to get sums of squares of ...
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### Derive the expectation and variance of squared sample correlation: delta-method or else?

I would like to obtain the expectation and variance of the squared Pearson sample correlation ($\operatorname{E}(R_{lk}^2)$ and $V(R_{lk}^2)$) between two random variables $l$ and $k$ following a ...
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### Comparing Adjusted $R^2$ Between Totally Different Models

I'm curious as to what extent adjusted $R^2$ can be used to compare models. If I had two different data sets and completely different models for both data sets, could I say something like the the ...
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### Calculate $R^2$ given estimated coefficients and $N$ only

We have a simple regression equation $y=a+bx$, where $a,b$ were estimated via OLS -- we know these values. Suppose the number of observations $N=25$ is given. Is it true, that we cannot calculate $R^2$...
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### SPSS R^2 for Negative Binomial

I am running a negative binomial regression in SPSS and wondered if there is any way to display R^2 statistics, as would be the case if binary/linear regression was conducted?
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I understand the r2 metric, being 1- (rss /tss) where rss = sum of squared residuals and tss = total sum of squares I understand how to weight this, such as when each row is a population, and some ...
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### How can I improve R2 score in my regression model? Predicting House Prices

I have trained some data on a House Pricing dataset. and I'm getting a not-so-bad R-2 score of nearly 0.5 as you can see below: I wanted to ask how can I improve this R-2 Score and get more precise ...
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### How to evaluate an Earth system model in light of the spatial variability of observed variables?

Context My effort is to evaluate the performance of a physics-based numerical model to determine how well it simulates different state variables of a soil column (1D inside the model). The temporal ...
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### Is p-value of R-squared and adjusted R-squared a thing?

I'm currently reading a paper which utilises a multiple regression and reports the adjusted $R^2$ with a p-value, and I'm wondering what this p-value refers to. Can you calculate p-values for adjusted ...
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