The data below are for 30 people. Theindependent variable is “age” and the dependent variable is“systolic blood pressure.” Also, note that the variables arepresented in the form of vectors that can be used in R.

age=c(39,47,45,47,65,46,67,42,67,56,64,56,59,34,42,48,45,17,20,19,36,50,39,21,44,53,63,29,25,69)

systolic.BP=c(144,20,138,145,162,142,170,124,158,154,162,150,140,110,128,130,135,114,116,124,136,142,120,120,160,158,144,130,125,175)

1. Using R, develop and show a scatterplot of systolic bloodpressure (dependent variable) by age (independent variable), andcalculate the correlation between these two variables.
2. Assume that these data are “straight enough” to model using alinear regression line. Develop and show that model (write out themodel in the terms of the problem), and also show in a plot theline that best fits these data.
3. Plot the residuals and comment on what you see as to howappropriate the model is.
4. Using a boxplot, determine if there are any outliers insystolic blood pressure. If so, point out which points areoutliers, if any.
5. Assuming there is at least one outlier in systolic bloodpressure, remove that outlier and re-do parts a) through c) againusing the remaining data without the outlier(s). State and commenton this second model.
6. In your second model, explain in the context of age andsystolic blood pressure what the slope of your fitted line means.Also, for your second model, calculate R² (thecoefficient of determination), and explain what that means in thecontext of your second model.