mm The family,I of models called generalized linear models can be used to fit regression models to: Poisson distribution normally distributed data Gaussian data non-Gaussian data In multiple regression. the correlation of each independent variable with the dependent variable is the correlation when: the effect ofthe other independent variables has been removed. the distribution ofthe error terms is reasonably close to a normal distribution and the error terms have approximately constant variance. 069 we use an estimation procedure that places less emphasis on outlying observations in the data. an increase in one variable is associated with an increase in another. (96) Question 9 2 Points Logistic regression analysis predicts the values on one dependent variable from one or more independent variables when the dependent variable is: A non-linear B correlated with the independent variable C dichotomous, i.e., it divides the respondents or cases into two exclusive groups. D continuous Question 10 2 Points The research questions addressed by survival analysis are concerned with the time taken for an event to happen: A with the use of transformations of one or both of the original variables in the regression model. B from the point in time at which observations begin. C when a particular independent variable predicts the outcome of the dependent variable. when the nature of the relationship between the independent variables and the dependent variable do not have to be normally distributed