we will perform regression analysis using the weight of the bears to predict their age. For this problem you will use the whole data set, not the one separated by sex. That means, you will have to use the variables bears$Weight and bears$Age (a) (1) Create a scatter plot of Age vs Weight using the function plot(x,y). You must also add an appropriate title (including your name) using the main = "title here" argument, and change the axis labels using xlab="Weight" and ylab="Age". (b) (1) Comment on the association between age and weight, as seen in your scatter plot. (c) (2) Calculate and interpret the correlation coefficient using the cor(x,y) function. (d) (1) Use the code below to create and summarize the linear model. Note: order matters here and this code will only work as is if you have named your original data set "bears". model = lm(bears$Age ~ bears$Weight) summary(model) (e) (1) Identify the regression equation from the R output. (f) (1) Identify the coefficient of determination from the R output