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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 ...
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?
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.
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 ...
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.
regression - Interpreting the residuals vs. fitted values plot for ...
Consider the following figure from Faraway's Linear Models with R (2005, p. 59). The first plot seems to indicate that the residuals and the fitted values are uncorrelated, as they should be in a
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...
regression - Maximum likelihood method vs. least squares method - Cross ...
What is the main difference between maximum likelihood estimation (MLE) vs. least squares estimaton (LSE) ? Why can't we use MLE for predicting $y$ values in linear ...
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