How to describe or visualize a multiple linear regression model
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 me how to …
regression - What does it mean to regress a variable against another ...
Dec 4, 2014 · When we say, to regress Y Y against X X, do we mean that X X is the independent variable and Y the dependent variable? i.e. Y = aX + b Y = a X + b.
Why are regression problems called "regression" problems?
I was just wondering why regression problems are called "regression" problems. What is the story behind the name? One definition for regression: "Relapse to a less perfect or developed state."
Can I merge multiple linear regressions into one regression?
Oct 3, 2021 · Although one can compute a single regression for all data points, if you include model assumptions such as i.i.d. normal errors, the for all points combined can't be "correct" if the four …
Why not approach classification through regression?
86 "..approach classification problem through regression.." by "regression" I will assume you mean linear regression, and I will compare this approach to the "classification" approach of fitting a logistic …
Rules of thumb for minimum sample size for multiple regression
Would you suggest an alternative rule of thumb for minimum sample size for multiple regression? Alternatively, what alternative strategies would you suggest for determining minimum sample size for …
DFBETA in regression model diagnostics of influential points
Feb 4, 2025 · Belsley (1980) mentioned how DFBETA are calculated for linear regression models "DFBETA values are usually calculated via equations that relate the least-squares fit of a …
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?
Newest 'regression' Questions - Cross Validated
Q&A for people interested in statistics, machine learning, data analysis, data mining, and data visualization
When is it ok to remove the intercept in a linear regression model ...
Hence, if the sum of squared errors is to be minimized, the constant must be chosen such that the mean of the errors is zero.) In a simple regression model, the constant represents the Y-intercept of the …