The accompanying data was read from a graph. The independent variable is SO, deposition rate (mg/m=/d) and the dependent variable is steel weight loss (g/m-). Use the code below to construct a scatterplot of the bivariate data, fit a simple linear regression model, and calculate the correlation coefficient between the two variables. X=c(13, 18, 35, 43, 45, 110) y=c (280, 350, 460, 500, 560, 1140) # Construct a scatterplot using R. plot (x, y) # Calculate the least squares regression line mod = Im(y~x) summary (mod) # Correlation cor (x, y)Fill in the Blanks Type your answers in all of the blanks and submit The estimated regression equation has the form y = B, + B, X. From the R output give the parameter estimates. Round all numerical values to two decimal places. Bo = Type your answer here B1 = Type your answer hereWhat is the correlation coefficient r? (Round your answer to three decimal places.) Type your numeric answer and submit Unanswered . 3 attempts left Submit Question 5e. Bivariate Data Homework . Unanswered Fill in the Blanks Type your answers in all of the blanks and submit Because the largest x value in the sample greatly exceeds the others, this observation may have been very influential in determining the equation of the line. Delete this observation and recalculate the equation. (Round all numerical values to two decimal places.) Let the new estimated equation be denoted using the following notation. y* = Bo + Bix Bo = Type your answer here B1 = Type your answer here