The Project 1 healthcare-dotosetstrokedataA contains the health metrics for 100 randomly selected individuals. The variables recorded are gender, age, hypertension, heart-d isease, marriage status, work type, residence type, average glucose level, BMI, smoking status, and whether the person ever had a stroke. [Some of the categorical variables have been coded in binary format such that True = 1 and False :0] The following are your assigned variables based on the rst letter of your last name: A-M Categorical variables: Gender and Stroke Status Quantitative variables: Age, BMI Categorical varia bl es: Gender a nd Hea rt Disease Quantitative variables: Age, Glucose levels For this project you will be asked to perform the appropriate analysis to explore the relationship between two categorical variables and separately Mo quantitative variables. For most of the questions, you will want to use technology to perform the computations, either Excel, a TI calculator, or the software available with the text. Upload your completed project to the appropriate place in Gradescope by the due date. 1. {5 pts} Perform a five-number summary for one of your quantitative variables and create a box plot. 2. {2 pts} For the quantitative variable in question 1 calculate the upper, lower fence and test for outliers. 3. {5 pts} Select one of the categorical variables and create a frequency distribution along with an appropriate graphical display. Steps 4-5 involve establishing an association between two categorical variables. 4. {5 pts} Using the two categorical variables that where assign to you create a two-way table summarizing the data. 5. {5 pts} Depending on the categorical variables you were assigned is there an association between gender and {Stroke or heart disease}? Explain in detail. Steps 6 13 involves correlations between two quantitative variables. 599 1|]. 11. 12. 13. 14. 15. 16. 1?. 18. {3 pts} Before you make any graphs or perform any calculations, what kind of association do you expect between the two variables Age and BMI or Age and Glucose levels? Explain why this is your expectation. {2 pts} Which variable is the explanatory variable, and which is the response variable? {3 pts} Create a scatterplot of the two variables and add the trendline. {2 pts} Compute the value of the correlation coefficient, r. {3 pts} Describe the linear association, strength, and type of relationship between the two variables. How did you determine the linear association? {3 pts} Compute the equation of the regression line and add the line to the scatterplot. {2 pts] Interpret the meaning of the slope of the regression line in this context. Explain {2 pts} Interpret the meaning of the yintercept of your regression line in this context. Does it have meaning? Explain. {2 pts} Compute the means for each of the variables and verify that that point is on the regression line by plugging the mean value of the explanatory variable into the equation for the regression line. {3 pts} What is the expected value {predicted 9} for your response variable for an individual with age 55? {2 pts} For the individual in row 9? who has an age of 55 compute the residual and explain what this value tells you about your data and the regression line. {4 pts) Compute R2 and explain both what this tells you in terms of how well the line ts the data and in terms of explained variability. {3 pts} How good do you feel about the regression line's ability to predict values, do you have any concerns about applying a linear regression? Explain your reasoning in detail