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True.
Correlation is a measure of association between two variables and the variables are not designated as dependent or independent. Simple regression is used to examine the relationship between one dependent and one independent variable. It goes beyond correlation by adding prediction capabilities.
line that measures the slope between dependent and independent variables
Yes. In fact, in multiple regression, that is often part of the analysis. You can add or remove independent variables to the model so as to get the best fit between what values are observed for the dependent variable and what the model predicts for the given set of independent variables.
In cases wherethe dependent variable can take any numerical value for a given set of independent variables multiple regression is used.But in cases when the dependent variable is qualitative(dichotomous,polytomous)then logistic regression is used.In Multiple regression the dependent variable is assumed to follow normal distribution but in case of logistic regression the dependent variablefollows bernoulli distribution(if dichotomous) which means it will be only0 or 1.