1- Here is data with y as the response variable. X: 68.2, 62.4, 48.9, 55.6, 53.6, 58.1, 50.7, 51.4, 135.8, 52.1 Y: 84, 75, 73.3, 79.7, 78.3, 78, 75.6, 76.9, 81.2, 74.5 1. Make a scatter plot of this data. Which point is an outlier? Enter your answer as an ordered pair, for example (a,b), including the parentheses. 2. Find the regression equation for the data set without the outlier. Enter as an equation of the form y=a+bx. Round the slope and y-intercept to three decimal places. 3. Find the regression equation for the data set with the outlier. Enter as an equation of the form y=a+bx. Round the slope and y-intercept to three decimal places. 4. Is this outlier an influential point? Yes, the outlier appears to be an influential point. No, the outlier does not appear to be an influential point. Question 2- Run a regression analysis on the following bivariate set of data with y as the response variable. X: 41.9, 65.9, 10.3, 55.3, 37.1, 18.6, 59.8, 47, 24.8, 42.2 Y: 64.7, 67.7, 91.1, 58.7, 55.8, 99.8, 42.6, 79.7, 79.2, 68.6 Find the correlation coefficient and report it accurate to three decimal places. r = What proportion of the variation in y can be explained by the variation in the values of x? Report answer as a percentage accurate to one decimal place. (If the answer is 0.84471, then it would be 84.5%...you would enter 84.5 without the percent symbol.) r = % Based on the data, calculate the regression line (each value to three decimal places) y =____ x + ______ Predict what value (on average) for the response variable will be obtained from a value of 25.3 as the explanatory variable. Use a significance level of =0.05 to assess the strength of the linear correlation. What is the predicted response value? (Report answer accurate to one decimal place.) y =