Linked Questions

9
votes
2answers
6k views

How can $R^2$ have two different values for the same regression (without an intercept) [duplicate]

My question is multifaceted. So I'll start by asking my question and then explain what has caused me to ask this question. How can I calculate the coefficient of determination for a linear ...
2
votes
1answer
3k views

Use squared correlation in regression without intercept [duplicate]

If I want to compare the goodness-of-fit of two regression models, with and without intercept, is it valid to compare the squared correlation coefficient between the fitted values and the data? Since ...
4
votes
1answer
1k views

Is it ok to remove the intercept in a linear regression model (OLS) if the results are really good? [duplicate]

So I've gone through this SE question and all the answers where the general consensus is that you should never remove the intercept of the linear regression model. The most upvoted answer says: The ...
2
votes
2answers
321 views

When forcing intercept to zero, how R-squared is changed? [duplicate]

I have some questions. In a linear model, I want to force intercept to zero. The program (I used JMP) does not provide R-squared when intercept becomes zero. So, I calculated R-squared by myself by ...
1
vote
0answers
549 views

Coefficient of Determination (R-Squared) definition in Matlab [duplicate]

First of all, I have to say that my knowledge of statistics is very basic. I was trying to fit data with a linear regression in Matlab, and I came across the problem of $R^2$ definition. I am using ...
0
votes
0answers
497 views

How could forcing my regression line to go through the origin increase the R^2? [duplicate]

I created the scatterplot on the left in Tableau and ran the regression line, which resulted in an R^2 of 0.63 (confirmed this in excel as well). Then, I used the "Force y-intercept to zero" option ...
4
votes
1answer
159 views

Why does R-Squared change with a no-intercept model? [duplicate]

Suppose I have one binary predictor $x$ and I fit an OLS model: $$y = \alpha + \beta I(x=1) + \epsilon$$ Alternatively I can fit the following model $$y = \beta I(x=1) + \beta I(x=0) + \epsilon$$ Why ...
0
votes
1answer
237 views

Interpreting of difference between R lm() with intercept and without it? [duplicate]

I have applied the lm() to a data set. The independent variables are categorical. First, I use lm() with intercept and I got the next results: ...
0
votes
1answer
176 views

Which regression model to choose? [duplicate]

I have two models, one lm(y ~ x1 + x2 + 0) which gives me a close to 0.90 something $R^2$ and another model lm(y ~ x1 + x2) ...
3
votes
1answer
115 views

linear model without intercept : wrong r-square value? [duplicate]

R linear model function lm looks like have a bug. with no intercept term. I want to know this is really a bug or my mistake on something... ...
1
vote
0answers
36 views

Computation of R-squared with lm() in R [duplicate]

Confusion on difference between the $R^2$ results from the lm() function in R and from the Equation $1-rss/sst$ (1) Ref: https://onlinecourses.science.psu....
1
vote
0answers
36 views

Zero Intercept Model Interpretation [duplicate]

I am supposed to run a regression of Medical Expenditure on several explanatory variables like income, no of illnesses, age and also some dummy variables like gender differentiating dummy, dummy for ...
1
vote
0answers
19 views

Why do we not get an R squared value for the intercept only term? [duplicate]

When I try to fit an intercept only model in R, why do I need get an R squared? I can see from the formula of the adjusted R squared that this would be 0, but this isn't shown either.
144
votes
9answers
155k views

When is it ok to remove the intercept in a linear regression model?

I am running linear regression models and wondering what the conditions are for removing the intercept term. In comparing results from two different regressions where one has the intercept and the ...
39
votes
6answers
20k views

Why do we need multivariate regression (as opposed to a bunch of univariate regressions)?

I just browsed through this wonderful book: Applied multivariate statistical analysis by Johnson and Wichern. The irony is, I am still not able to understand the motivation for using multivariate (...

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