Scatterplot of daily cycling distances and type of climb: Everysummer, the touring company America by Bicycle conducts the “CrossCountry Challenge,” a 7-week bicycle journey across the UnitedStates from San Francisco, California, to Portsmouth, NewHampshire. At some point during the trip, the exhausted cyclistsusually start to complain that the organizers are purposelyplanning for days with lots of hill and mountain climbing tocoincide with longer distances. The tour staff counter that norelation exists between climbs and mileage and that the route isorganized based on practical issues, such as the location of townsin which riders can stay. The organizers who planned the route(these are the company owners who are not on the tour) say thatthey actually tried to reduce the mileage on the days with theworst climbs. Here are the approximate daily mileages and climbs(in vertical feet), as estimated from one rider’s bicyclecomputer.

Mileage Climb Mileage Climb Mileage Climb 83 600 69 2500 102 2600 57 600 63 5100 103 1000 51 2000 66 4200 80 1000 76 8500 96 900 72 900 51 4600 124 600 68 900 91 800 104 600 107 1900 73 1000 52 1300 105 4000 55 2000 85 600 90 1600 72 2500 64 300 87 1100 108 3900 65 300 94 4000 118 300 108 4200 64 1500 65 1800 97 3500 84 1500 76 4100 91 3500 70 1500 66 1200 82 4500 80 5200 97 3200 77 1000 63 5200 92 3900 53 2500

1. Construct a scatterplot of the cycling data, putting mileage onthe x-axis. Be sure to label everything and include atitle.
2. We haven’t yet learned to calculate inferential statistics onthese data, so we can’t estimate what’s really going on, but do youthink that the amount of vertical climb is related to a day’smileage? If yes, explain the relation in your own words. If no,explain why you think there is no relation.
3. It turns out that inferential statistics do not support theexistence of a relation between these variables and that the staffseems to be the most accurate in their appraisal. Why do you thinkthe cyclists and organizers are wrong in opposite directions? Whatdoes this say about people’s biases and the need for data