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 …

Dec 23, 2016 · 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 …

Dec 4, 2014 · Those words connote causality, but regression can work the other way round too (use Y to predict X). The independent/dependent variable language merely specifies how one …

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Nov 14, 2010 · 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 …

For a simple logistic regression model like this one, there is only one covariate (Area here) and the intercept (also sometimes called the 'constant'). If you had a multiple logistic regression, …

Collinearity in regression: a geometric explanation and implications The first picture below shows a normal regression situation with two predictors (we'll speek of linear regression).

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 …

Oct 17, 2014 · The question is asking for the difference between logit and logistic regression. If the parameters returned are less comprehensive or more comprehensive isn't going to render …

Jan 15, 2016 · I have fish density data that I am trying to compare between several different collection techniques, the data has lots of zeros, and the histogram looks vaugley appropriate …