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I'm trying to fit a multiple linear regression model to my data with couple of input parameters, say 3. Dec 4, 2014when 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 was just wondering why regression problems are called "regression" problems.

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. 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?

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. Sample size calculation for logistic regression is a complex problem, but based on the work of peduzzi et al. I am trying to perform a multiple regression in r.

For multiple regression, you have some theory to suggest a minimum sample size.