Y-variable X-variable 2.25 3 3.75 6 6.2 9 7.8 12 10.1 15 12 18 Assume the above data-points are used to estimate the equation: Y=0 + 1X + . 1) Calculate the estimated values of 1 and 0. 2) For each observation, calculate the fitted (or predicted) value of Y. 3) For each observation, calculate the residual. 4) Calculate the total sum of squares, explained sum of squares and residual sum of squares. 5) Calculate R2. 6) Now that you have calculated the formula for 1, please explain a. What would happen to your calculated (estimated) 1 if Y had the same value for all observations? b. What would happen to your calculated (estimated) 1 if X had the same value for all observations? 2) A research project used a sample of almost 1400 singleton, new-born infants to examine whether infant birthweight was associated with smoking during pregnancy by the mother. The project used simple OLS regression. The equation is: Yi= 0 + 1Xi + u The outcome variable is the birthweight of the ith infant, measured in ounces. The x- variable of interest is the average number of cigarettes per day that the ith mother reported smoking during pregnancy