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There is multicollinearity in regression when the variables are highly correlated to each other. For example, if you have seven variables and three of them have high correlation, then you can just use one them in your dependent variable rather than using all three of them at the same time. Including multicollinear variables will give you a misleading result since it will inflate your mean square error making your F-value significant, even though it may not be significant.
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What is the difference between multiple regression and logistic regression?
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.
Can dummy variables be used in multiple linear regression analysis?
Yes they can.
Multiple regression analysis examines the relationship of several dependent variables on the independent variable?
True.
How are beta coefficients interpreted differently for regression and multiple regression?
Beta is just the slope (B0 is the y-intercept), and you have Bn coefficients where n is the number of regressors. In other words, it is the amount of change in y you would expect with a given change in x. When you deal with multiple regression, you will have a matrix (just one column though, so a vector) of beta values corresponding to your regressors.
What is the adjective of the word regression?
of, pertaining to, or determined by regression analysis: regression curve; regression equation. dictionary.com
