Using the Framingham Heart Study dataset provided, perform the ANOVA multivariab

Using the Framingham Heart Study dataset provided, perform the ANOVA multivariable linear regression analysis using BMI as a continuous variable. Before conducting the analysis, be sure that all participants have complete data on all analysis variables. Describe how each characteristic is related to BMI. Discuss the alpha, p-value, and F statistics and what you notice about their significance levels. Discuss any differences that you notice concerning the significance of any of the independent variables. H0 The BMI is not related to the patient characteristics of Glucose, Angina, Stroke, CVD, and Hypertension in the Framingham Heart Study. (Null Hypothesis) H1 The BMI is related to the patient characteristics of Glucose, Angina, Stroke, CVD, and Hypertension in the Framingham Heart Study. (Alternative Hypothesis) Upload both Excel sheets into RStudio if you are using RStudio to analyze the dataset. (Refer to Chapters 7 & 12 in Introductory Statistics with R orpages 111-122 in EXCEL statistics A quick guide T.Test). Conduct the simple linear regression (ANOVA) by using the Excel Regression tool in the Data Analysis Toolpak. Ensure to submit the following requirements for the assignment: Present your findings in a Word document by copying and pasting the ANOVA table into the document. Your paper must be written with a title page, an introduction, a discussion where you interpret the meaning of the ANOVA test, and a conclusion should be included. Your submission should be 3-4 pages to discuss and display your findings. Provide support for your statements with in-text citations from a minimum of two scholarly, peer-reviewed articles. One of these sources may be from the class readings, textbook, or lectures, but the others must be external. The Saudi Digital Library is a good place to find these sources and should be your primary resource for conducting research. Follow APA 7th edition and Saudi Electronic University writing standards. RE: Module 9 CT asssignment #3. High similarity scores are expected if done correctly. There are 3 potential options to successfully complete this assignment: 1. Perform the Multivariable Linear Regression Statistic with the 5 independent variables and dependent variable (BMI). Report the P value, Y=mx+b regression formula, identify the beta weights associated with each independent variable to determine which has the most and least influence on BMI, and support the correct hypothesis with rationale. Make sure to remove any blank/missing values of all variables or you will get an error message when trying to run regression. *This was demonstrated in Live Session #4. 2. Perform the ANOVA inferential statistic with the 5 independent variables and dependent variable (BMI). Report the P value, and F stattistics associated with all independent variables, and determine/report which variable has the most vs. least difference based on BMI, and support the correct hypothesis with rationale. 3. Do both the Multivariable Linear Regression Statistic and ANOVA inferential statistic per above. The final product will be anywhere from 1-4 pages long typically, Dr. Eric