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What should the proportions be in a regression?
This generally translates to all your data being between .2 and .8 (although I’ve heard that between .3-.7 is better). If this holds, you don’t have to worry about the two objections. You do have a linear relationship, and you won’t get predicted values much beyond those values–certainly not beyond 0 or 1.
Which is the best way to do regression?
The simplest approach is to do a linear regression anyway. This approach can be justified only in a few situations. 1. All your data fall in the middle, linear section of the curve. This generally translates to all your data being between .2 and .8 (although I’ve heard that between .3-.7 is better).
What is the purpose of regression in statistics?
In statistics, regression analysis is a statistical technique for estimating the relationships among variables. It includes many techniques for modeling and analyzing several variables when the focus is on the relationship between a dependent variable and one or more independent variables.
When to use logistic regression for percentages and counts?
One key consideration is the dependent variable. For linear models, the dependent variable doesn’t have to be normally distributed, but it does have to be continuous, unbounded, and measured on an interval or ratio scale. Percentages don’t fit these criteria. Yes, they’re continuous and ratio scale.
Which is the first chapter of a regression analysis?
This first chapter will cover topics in simple and multiple regression, as well as the supporting tasks that are important in preparing to analyze your data, e.g., data checking, getting familiar with your data file, and examining the distribution of your variables.
Which is the dependent variable in a regression?
My dependent variable is Probability of species being extant, so bounded between 0 and 1. It has a J-shaped distribution – the main peak around 0.9 and a secondary peak around 0.1. I have 2 explanatory variables and 2 random factors. I was wondering about trying a beta regression?