Jeremy is on the planning committee for the rock climbing club. he is putting together a trip where members can go outdoor rock climbing. he is trying to determine how high the group should climb and how long the trip should last. he calls multiple parks in the area that offer rock climbing and collects data on the height of the rock formations and the average time it takes people to reach the top and come back down. the data he found is shown.
part a) use the graphing tool to determine the line of best fit for the scatter plot.
part b)
give the equation, slope, and y-intercept for the line of best fit. explain what this information tells jeremy about the trip he’s planning.
part c)
examine the residual plot of the data. does the residual plot indicate that a linear function is the best function to use to model the data? or does it indicate that a nonlinear function would be a better fit? give your reason.
part d)
use the graphing tool to determine the correlation coefficient, and interpret what it means in this situation.
part e)
type the correct answer in each box. round your answers to the nearest tenth.
the table shows the heights of three different rock formations that jeremy is considering. use the line of best fit to predict how long it will take to climb and come back down the three rock formations.
part f)
jeremy has heard a lot of people in the club talking about tackling a 950-foot rock formation. jeremy has set a limit that they won’t climb anything that takes longer than 7 hours, so they have enough time to travel to and from the place. will it be possible to climb a 950-foot rock formation within jeremy’s time constraint? explain why or why not.