Explain the assumptions of Linearity, Sampling independence, Normality, and Homoscedasticity

1. Explain the assumptions of Linearity, Sampling independence, Normality, and Homoscedasticity (or equal variance). (30 points)
1. How would you test whether these have been met? (Note: for the exam you do not need to test these assumptions)
2. Using SPSS, test the assumption of Linearity between the independent and dependent variables.
3. Using SPSS, test the assumption of Normality for the dependent variable.
2. Conduct a multiple linear regression using SPSS. Provide relevant SPSS output and assess the statistical significance of the effects of mothers Age, BMI, and Coffee (Cups per Day) on Birth weight. (30 points)
3. Explain the practical implications of your finding. Include a reference to the R square of the model in your discussion. (20 points)
4. Discuss whether or not there is interaction (effect modification) first between Age and BMI and second between BMI and Coffee. (20 points)
Reference
Daniel, WW & Cross, CL. (2013). Biostatistics: A Foundation for Analysis in the Health Sciences. Hoboken, NJ: Wiley
Krantz, M. J., Coronel, S. M., Whitley, E. M., Dale, R., Yost, J., & Estacio, R. O. (2013). Effectiveness of a community health worker cardiovascular risk reduction program in public health and health care settings. American Journal of Public Health, 103(1), e19e27.
Weil, M., Bressler, J., Parsons, P., Bolla, K., Glass, T., & Schwartz, B. (2005). Blood mercury levels and neurobehavioral function. JAMA, 293(15), 18751882
Williamson, D. F., Madans, J., Anda, R. F., Kleinman, J. C., Giovino, G. A., & Byers, T. (1991). Smoking cessation and severity of weight gain in a national cohort. New England Journal of Medicine, 324(11), 739745.
Huff, D., & Geis, I. (1954). How to lie with statistics. New York, NY: Norton.
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