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Why are regression problems called "regression" problems?
Origin of 'regression' The term "regression" was coined by Francis Galton in the 19th century to describe a biological phenomenon. The phenomenon was that the heights of descendants of tall ancestors tend to regress down towards a normal average (a phenomenon also known as regression toward the mean)(Galton, reprinted 1989).
regression - What does it mean to regress a variable against another ...
As an example, the data is X = 1,...,100. The value of Y is plotted on the Y axis. The red line is the linear regression surface. Personally, I don't find the independent/dependent variable language to be that helpful. Those words connote causality, but regression can work the other way round too (use Y to predict X).
regression - Linear model with both additive and multiplicative effects ...
$\begingroup$ in the top answer to the following unrelated question, a linear regression plot (second graph) shows a non-linear regression line shown in red. how can a linear regression model produce a non-linear curve for a regression line when we know that regression lines from a linear regression model can only be straight?
regression - What intuitively is "bias"? - Cross Validated
In regression we can get biased estimators of slopes by doing stepwise regression. A variable is more likely to be kept in a stepwise regression if the estimated slope is further from 0 and more likely to be dropped if it is closer to 0, so this is biased sampling and the slopes in the final model will tend to be further from 0 than the true slope.
regression - How to Interpret Interaction Between Two Categorical ...
I am having some difficulty attempting to interpret an interaction between two categorical/dummy variables. For example, lets say there is an interaction term between an individual's gender and he
regression - Interpret log-linear with dummy variable - Cross Validated
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 question is how do I interpret...
regression - How to tell if a model is identifiable ... - Cross Validated
There are two types of (non)-identifiabilities: Structural identifiability. This refers to an intrinsic property of a model, for which different combinations of its parameters would yield exactly the same output.
regression - Why does a time series have to be stationary? - Cross ...
This multiple regression technique is based on previous time series values, especially those within the latest periods, and allows us to extract a very interesting "inter-relationship" between multiple past values that work to explain a future value.
regression - Condition Number for solving a linear problem using the ...
Belsley, Kuh, and Welsch (1980), Regression Diagnostics (J. Wiley) have a nice exposition of this, so I will quote them verbatim. Beware: their notation differs from that of the question. Beware: their notation differs from that of the question.
regression - Building a linear model for a ratio vs. percentage ...
Echoing the first answer. Don't bother to convert - just model the counts and covariates directly. If you do that and fit a Binomial (or equivalently logistic) regression model to the boy girl counts you will, if you choose the usual link function for such models, implicitly already be fitting a (covariate smoothed logged) ratio of boys to girls.
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