MATH 225N Week 8 Discussion: Correlation and Regression
MATH 225N Week 8
MATH225N
MATH 225N
Discussion: Correlation and Regression
MATH 225N Week 8
... [Show More] Discussion: Correlation and Regression
Initial Post Instructions
If a regression analysis was to be completed on body mass index (BMI), what could be an independent variable in that analysis? Why? If we could, what other independent variables should be included in the analysis? What statistic(s) would show the value of that regression in understanding BMI?
Alternatively, find an article that uses regression analysis to study a medical concern. In that study, what was the dependent variable and what were the independent variable(s)? Further, how would you use this study to highlight the difference between correlations and causation?
NB: 2 Answers Displayed
Answer 1
According to out text, regression analysis "can provide an estimate of the magnitude of the impact of a change in one variable or another" (Holmes, Illowsky, & Dean, 2017). If regression analysis was to be completed on BMI, an independent variable associated in that analysis would be the height and weight, which is how the BMI is calculated. This is because as the body ages, the amount of body fat is typically greater than that of a younger person. Additionally, females typically have a higher percentage of body fat as opposed males. Other independent variables that could be included in the analysis would be physical activity, age, sex, build of body/cultures. Another statistic that would show the value of that regression in understanding BMI would be the amount of physical activity. The greater the amount of physical activity, the lower the BMI.
The article I researched that I found interesting regarding regression analysis discussed the correlation between cognitive vulnerability to depression and glycemic control in patients with type 2 diabetes. Other independent variables such as health history, comorbidities, smoking history, age, gender, alcohol use, and etc. were explored and analyzed as potential causative factors or correlations. The dependent variable in the study was type 2 diabetes. In the article, "in the final multivariate regression model, 44% of the variance in HbA1c values could be explained by the chosen variables" (Ma et al., 2018).
References
Holmes, A., Illowsky, B., & Dean, S. (2017). Introductory Business Statistics. Retrieved from https://openstax.org/details/books/introductory-business-statistics (Links to an external site.)
(Links to an external site.)Ma, Y., Li, X., Zhao, D., Wu, R., Sun, H., Chen, S., … Gao, S. (2018). Association between cognitive vulnerability to depression - dysfunctional attitudes and glycaemic control among in-patients with type 2 diabetes in a hospital in Beijing: a multivariate regression analysis. Psychology, Health & Medicine, 23(2), 189–197. https://doi.org/10.1080/13548506.2017.1339894
Answer 2
For the regression analysis on body mass index (BMI) an independent variable could be activity level. Activity level/exercise (length of time) is valuable data because a person’s activity level has a direct effect on weight control and BMI. For example, a person with a sedentary lifestyle, most times than not will have a higher BMI than that of a person that is athletic. Another independent variable that should be included is diet. The correlation coefficient between the dependent and independent variable, show the connection among the variables.
The article I found is an analysis between level of professional education and handwashing compliance. In the study the independent variable is level of education and the dependent variable is handwashing compliance. The study resulted in an inverse correlation. Negative correlation: The two variables tend to change in opposite directions, with one increasing while the other decreases (Bennett, 2013, p. 237). The correlation coefficient identifies the relationship between variables while the causation explains these relationships. The causation can be identified by the experiment when one independent variable changes while holding another variable constant. For this study the nurses’ compliance increased while other staff, ex. Medical residents decreased.
References
Bennett, J.O., Mario, F. T., William, L.B. (2018), Statistical Reasoning for Everyday Life (5th ed.). Boston: Pearson
Duggan, J., et al. (2008). Inverse Correlation Between Level of Professional Education and Rate of Handwashing Compliance in a Teaching Hospital: Infection Control and Hospital Epidemiology, 29(6):534-8. Doi: 10.1086/588164 [Show Less]