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Regression with multiple dependent variables? - Cross Validated
Is it possible to have a (multiple) regression equation with two or more dependent variables? Sure, you could run two separate regression equations, one for each DV, but that doesn't seem like it ...
regression - When is R squared negative? - Cross Validated
Also, for OLS regression, R^2 is the squared correlation between the predicted and the observed values. Hence, it must be non-negative. For simple OLS regression with one predictor, this is equivalent to the squared correlation between the predictor and the dependent variable -- again, this must be non-negative.
How should outliers be dealt with in linear regression analysis ...
What statistical tests or rules of thumb can be used as a basis for excluding outliers in linear regression analysis? Are there any special considerations for multilinear regression?
How to describe or visualize a multiple linear regression model
Then this simplified version can be visually shown as a simple regression as this: I'm confused on this in spite of going through appropriate material on this topic. Can someone please explain to me how to "explain" a multiple linear regression model and how to visually show it.
regression - Difference between forecast and prediction ... - Cross ...
I was wondering what difference and relation are between forecast and prediction? Especially in time series and regression? For example, am I correct that: In time series, forecasting seems to mea...
regression - Trying to understand the fitted vs residual plot? - Cross ...
A good residual vs fitted plot has three characteristics: The residuals "bounce randomly" around the 0 line. This suggests that the assumption that the relationship is linear is reasonable. The res...
correlation - What is the difference between linear regression on y ...
The Pearson correlation coefficient of x and y is the same, whether you compute pearson(x, y) or pearson(y, x). This suggests that doing a linear regression of y given x or x given y should be the ...
Multivariable vs multivariate regression - Cross Validated
One outcome, one explanatory variable, often used as the introductory example in a first course on regression models. multivariate multivariable regression. Multiple outcomes, multiple explanatory variable. This is the scenario described in the question. multivariate univariable regression. Multiple outcomes, single explanatory variable.
What's the difference between correlation and simple linear regression ...
In particular one piece of information a linear regression gives you that a correlation does not is the intercept, the value on the predicted variable when the predictor is 0. In short - they produce identical results computationally, but there are more elements which are capable of interpretation in the simple linear regression.
When conducting multiple regression, when should you center your ...
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 dividin...
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