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."
regression - What does it mean to regress a variable against …
Dec 4, 2014 · When we say, to regress $Y$ against $X$, do we mean that $X$ is the independent variable and Y the dependent variable? i.e. $Y =aX + b$.
regression - When is R squared negative? - Cross Validated
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 …
regression - Trying to understand the fitted vs residual plot?
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 …
How are regression, the t-test, and the ANOVA all versions of the ...
May 15, 2013 · I add another ANOVA version w/ 3 groups lower down to clarify that a 2-group situation isn't the only ANOVA case that can be understood as a regression; but the reg …
When conducting multiple regression, when should you center …
Jun 5, 2012 · In some literature, I have read that a regression with multiple explanatory variables, if in different units, needed to be standardized. (Standardizing consists in subtracting the mean …
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 model for all points combined can't be …
understanding of p-value in multiple linear regression
Regarding the p-value of multiple linear regression analysis, the introduction from Minitab's website is shown below. The p-value for each term tests the null hypothesis that the coefficient …
Multiple logistic regression power analysis - Cross Validated
But there appears to be very little documentation on multiple logistic regression models like my situation. I don't know how to do a more detailed power analysis for multiple logistic regression.
Why use linear regression instead of average y per x
Mar 23, 2017 · Wow. So why bother going through the linear regression formulas if you can just divide the mean of y with the mean of x?