Linked Questions

8
votes
2answers
5k 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
819 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 ...
1
vote
0answers
382 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
1answer
206 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
175 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) ...
0
votes
0answers
130 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 ...
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
32 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 ...
119
votes
9answers
112k 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 ...
28
votes
6answers
12k 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 (...
24
votes
8answers
51k views

When forcing intercept of 0 in linear regression is acceptable/advisable [duplicate]

I have a regression model to estimate the completion time of a process, based on various factors. I have 200 trials of these processes, where the 9 factors being measured vary widely. When I perform a ...
38
votes
1answer
15k views

Manually calculated $R^2$ doesn't match up with randomForest() $R^2$ for testing new data

I know this is a fairly specific R question, but I may be thinking about proportion variance explained, $R^2$, incorrectly. Here goes. I'm trying to use the ...
24
votes
1answer
8k views

Geometric interpretation of multiple correlation coefficient $R$ and coefficient of determination $R^2$

I am interested in the geometric meaning of the multiple correlation $R$ and coefficient of determination $R^2$ in the regression $y_i = \beta_1 + \beta_2 x_{2,i} + \dots + \beta_k x_{k,i} + \...
13
votes
2answers
52k views

Understanding dummy (manual or automated) variable creation in GLM

If a factor variable (e.g. gender with levels M and F) is used in the glm formula, dummy variable(s) are created, and can be found in the glm model summary along with their associated coefficients (e....

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