Feb 2, 2020 · Multivariable regression is any regression model where there is more than one explanatory variable. For this reason it is often simply known as "multiple regression". In the …

Nov 3, 2017 · In linear regression, we often get multiple R and R squared. What are the differences between them?

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 know how to calculate t-statistics and p-values for linear regression, but I'm trying to understand a step in the derivation. I understand where Student's t-distribution comes from, namely I can ...

another way of thinking about the n-2 df is that it's because we use 2 means to estimate the slope coefficient (the mean of Y and X) df from Wikipedia: "...In general, the degrees of freedom of …

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

Apr 30, 2019 · I have the following model: ln(y) = b0 + B1 X1 + B2 ln(X2) + B3 X3 My X1 is a dummy that can take the values 0, 1 and 2. The coefficient for the dummy 1 is -0.500. My …

Jan 17, 2017 · Just to complement what Chris replied above: The F-statistic is the division of the model mean square and the residual mean square. Software like Stata, after fitting a …

Aug 4, 2020 · I am running linear regression for a continuous variable (not standardized) with age and 2 other numeric continuous variables (not standardized), 2 categorical variables with 3 …

4 I'm not sure of the actual relationship of this to exponentially weighted moving linear regression, but a simple online formula for estimating an exponentially-weighted slope and offset is called …