Advanced Statistical Concepts And Business Analytics


Please answer each of the following questions in detail and provide examples for better clarity wherever applicable. Provide in-text citations. In answering the following questions please include choice of significance level and the effect of p-values

  • Explain the linear multiple regression model, the independent variables and the dependent variable, assumptions of the model, as well as the objectives
  • Given the data, what approach is taken to construct the model?
  • Explain the effect of multicollinearity in multiple regression, and how multicollinearity is detected?
  • Show that the estimates of the coefficients are unbiased estimates of actual values.
  • 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
  • How do you interpret the effect of significant coefficients?
  • How are the distribution of the observed residuals of the constructed model tested for normality?
  • What is the coefficient of determination, and what is its significance?
  • Why is the adjusted coefficient of determination used as an alternative assessment
  • How can the regression model be used for prediction?


1. Need to have at least 1 peer-reviewed article as the reference and textbook as the reference

2. Need in-text citation

3. Please find the attachments as the power points of the course for reference.

4. Textbook Information:

Bowerman, B., Drougas, A. M., Duckworth, A. G., Hummel, R. M. Moniger, K. B., & Schur, P. J.  (2019). Business statistics and analytics in practice (9th ed.). McGraw-Hill

ISBN 9781260187496

5. Please find the Course Learning Outcome list of this course in the attachment

6. Need to explain in detail and provide examples