The table below shows the amount of time each of the 15 students in an introductory philosophy class spent studying for the first exam, and the student's score on the exam out of 100. x (minutes spent studying) y (score on exam in points) \" \"m '_ To check this is entered correctly on your calculator, press [stat], go to CALC, and select "2:2-Var Stats". Run this on your two lists. When you scroll down the list, you should see ny=60430 Enter the data into your calculator and obtain a linear equation of best fit using the linear regression feature. Type the equation here, in the form 3; 2 mm + b. If necessary, round the values of m and b to three decimal places. Based on your regression equation, what score would you predict for a student who has studied for 1 hour and 20 minutes? Round your answer to a whole number of points. poi nts Based on your regression equation, how much time should a "typical" student spend studying if they wanted to score at least 95 points on the exam? Round your answer up to the next full minute. minutes Consider the following table, which shows a data set relating the number of full days hikers spent on the Appalachian trail {a very long trail that attracts ambitious hikers), and the number of miles they hiked along the trail. x (full days of hiking) y (miles hiked) F To check this is entered correctly on your calculator, press [stat], go to CALC, and select "2:2-Var Stats". Run this on your two lists. When you scroll down the list, you should see ny=49431 Enter this data into your calculator and obtain a linear equation of best fit using the linear regression feature. Type the equation here in y 2 mm + 1) form, rounding m and b to two decimal places. Based on your regression equation above, predict how many miles a hiker would be able to hike on the Appalachian trail if they planned to hike for 18 days. Round your answer to the nearest full mile. miles If a typical hiker wanted to see a solid 310-mile stretch of the Appalachian Trail, how many days should they plan to hike? Round up to the next full day. days