Explain effect of multicollinearity in logistic regression

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Logistic Regression

  1. Explain the logistic regression model, the independent variables and the dependent variable, assumptions of the model, as well as the objectives
  2. Explain the effect of multicollinearity in logistic regression, and how multicollinearity is detected?
  3. Explain the hypotheses on coefficients of the regression and how the results of testing these hypotheses are interpreted about significance of these coefficients? Include both unidirectional and bidirectional situations
  4. How do you interpret the effect of significant coefficients?
  5. How the distribution of the observed residuals of the constructed model are tested for normality?
  6. What is the coefficient of determination, and what is its significance?
  7. How can the regression model be used for prediction?

Reference no: EM132852933

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