Assignment: Advanced Statistical Concepts and Business Analytics
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?
Textbook: 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.
Format your assignment according to the give formatting requirements:
1. The answer must be double spaced, typed, using Times New Roman font (size 12), with one-inch margins on all sides.
2. The response also includes a cover page containing the title of the assignment, the course title, the student's name, and the date. The cover page is not included in the required page length.
3. Also include a reference page. The references and Citations should follow APA format. The reference page is not included in the required page length.