This is only an answer to the second part. (I did not calculate the correlation coefficient for the first part.)
With r = -.015 being so close to zero, I would not have any confidence in my answer.
A college football coach wants to know if there is a correlation between his players’ leg strength and the time it takes for them to sprint 40 yards. He sets up the following test and records the data:
Every day for a week, he counts how many times each player can leg press 350 pounds. The following week, he has each player sprint 40 yards every day. The table shows the average number of leg-press repetitions and the average 40-yard dash time (in seconds) for seven randomly selected players. What is the equation of the line of best fit? How many seconds should he expect a player to take to run 40 yards if that player can do 22 leg-press repetitions? Round any values to the nearest tenth, if necessary.
[] means space.
Leg Press(Reps) (x) 15 [] 18 [] 8 [] 30 [] 26[] 12 [] 21 []
40-Yard Dash(s) (y) 5.2 [] 6.3 [] 6.8 [] 8.2 [] 8.0 [] 5.3 [] 5.9 []
Also, I need help with this one please.
You use a line of best fit for a set of data to make a prediction about an unknown value. The correlation coefficient for your dataset is -0.015. How confident can you be that your predicted value will be reasonably close to the actual value?
Please give me a response that tells me how confident I will be and how close the answer is.
1 answer
2 answers