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 …

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 …

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 21, 2016 · When we say, to regress $Y$ against $X$, do we mean that $X$ is the independent variable and Y the dependent variable? i.e. $Y =aX + b$.

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?

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 …

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 …

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 …

Apr 15, 2016 · The word "regressed" is used instead of "dependent" because we want to emphasise that we are using a regression technique to represent this dependency between x …

None of the three plots show correlation (at least not linear correlation, which is the relevant meaning of 'correlation' in the sense in which it is being used in "the residuals and the fitted …