Does every variable need to be statistically significant in a ...
Oct 18, 2024 · I recently fit a regression model (ARIMAX) in which some variables (3) were statistically significant and some were not (1). I removed the statistically insignificant variables and refit the …
Multivariable vs multivariate regression - Cross Validated
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 simple …
regression - Why do we say the outcome variable "is regressed on" the ...
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 and y. So, this …
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 equivalent to …
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 …
Explain the difference between multiple regression and multivariate ...
There ain’t no difference between multiple regression and multivariate regression in that, they both constitute a system with 2 or more independent variables and 1 or more dependent variables.
correlation - What is the difference between linear regression on y ...
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 the ...
When conducting multiple regression, when should you center your ...
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 and dividin...
When to use negative binomial and Poisson regression
Sep 2, 2024 · When would one use a negative binomial regression and when would one use Poisson regression with respect to the mean and variance?
Why is Poisson regression used for count data?
Oct 4, 2013 · I understand that for certain datasets such as voting it performs better. Why is Poisson regression used over ordinary linear regression or logistic regression? What is the mathematical …