0 Question 1 v For the rst three problems, the regression equation is given to you. Practice Using the Equation to Make Conclusions and Predictions. Baseball regression line prediction: Suppose the equation for the regression line for the number of runs scored in a season, 3!, is given by y : i 750 + 4500113, where a: is the team's batting average. For a team with a batting average of 0.235, find the expected number of runs scored in a season. Round your answer to the nearest whole number. [:J Question Help: El Video Submit Question . Question 10 Interpret the slope of the regression line. Annual high temperatures (Celsius) in a certain location have been tracked for several years. Let X represent the number of years after 2000 and Y the high temperature. Based on the data shown below, the linear regression equation was calculated using technology. X y 5 38.85 6 38.56 39.37 8 38.28 g 39.59 10 43.3 11 45.01 12 42.62 13 44.23 14 46.64 15 46.25 The equation is y = 33.155 + 0.891c Interpret the slope: O For each additional 33.155 years, the annual high temperature will increase by 1 degree on average. O For each additional 0.891 years, the annual high temperature will increase by 1 degree on average. O For each additional year, the annual high temperature will increase by 0.891 degrees on average. O For each additional year, the annual high temperature will increase by 33. 155 degrees on average.Question 2 For the first three problems, the regression equation is given to you. Practice Using the Equation to Make Conclusions and Predictions. The following table shows retail sales in drug stores in billions of dollars in the U.S. for years since 1995. Year Retail Sales 0 85.851 3 108.426 6 141.781 9 169.256 12 202.297 15 222.266 Let y be the retails sales in billions of dollars in a years since 1995. A linear model for the data is y = 9.44x + 84.182. 220 210 200 190 180 170 160 150 140 130 120 110 100 90 3 6 9 12 804 15 A) Use the above scatter plot to decide whether the line of best fit, fits the data well. O The function is not a good model for the data O The function is a good model for the data. B) To the nearest billion, estimate the retails sales in the U. S. in 2012. billions of dollars. () Use the equation to find the year in which retails sales will be $245 billion..Question} V ( > For the rst three problems, the regression equation is given to you. Practice Using the Equation to Make Conclusions and Predictions. The table below shows the number of staterreg'istered automadc weapons and the murder rate for several Northwestern states. :I: 11.4 8.1 6.9 3.8 2.4 2.1 2.7 0.4 g 13.7 10.7 9.6 7.6 6.3 5.9 6.6 4.7 :l: = thousands of automatic weapons 1;: murders per 100,000 residents This data can be modeled by the equation I: = 0.82: + 4.32. Use this equation to answer the following; Special Note: I suggest you verify this equation by performing linear regression on your calculator. Use the equation with the values rounded to two decimal places to make your predictions. A) How many murders per 100,000 residents can be expected in a state with 4.9 thousand automatic weapons? Answer = :] Round to 3 decimal places. B) How many murders per 100,000 residents can be expected in a state with 6.5 thousand automatic weapons? Answer = :1 Round to 3 decimal places. Question 4 Practice finding the regression equation and correlation coefficient using technology. Based on the data shown below, calculate the regression line (each value to two decimal places) y = * + X y 3 1.73 4 1.64 5 3.95 6 4.06 7 5.17 8 2.08 4.59 10 5.4 11 3.51 12 2.32 13 5.33 14 4.54. Question 5 Based on the data shown below, calculate the correlation coefficient (rounded to three decimal places) X y 5 28.25 6 27.72 7 29.79 8 30.66 9 32.83 10 35.2 11 40.77 12 39.64Question 7