Can you show me how to deal with the problem step by step? Tallis is a graduate

Question

Can you show me how to deal with the problem step by step?

Tallis is a graduate student at Purdue. Each school day he commutes one hour to school and back. In preparation for his commute, he considered a new insurance policy on his car. The insurance company provided him a dataset on the price of the insurance (controlling for inflation) in U.S. dollars vs. length of time without incident. He then calculated the following prediction line: y 776.811-46273x. The corresponding coefficient of determination is 0.9135. Answer the questions on the next page 8. The data and scatterplot are below: Time without incident (in years) Policy Price (in dollars) 8 800700 645 642 622 600 550 530 410 Price of Insurance (US Dollars) vs. Length of Time without Incident (Years)

Explanation / Answer

a) The relationship between price and length of time without incident is negative correlation since slope < -46.273
The points are going from upward to downward

b) slope = -46.273 which is less than <0 so it is positive correlation
AS time without incident 1 year increase then price decrease is -46.273 dollars

c) Correlation determination r^2 = 0.9135 = 91.35% variation in the policy price is explained by time without incident

d) If 3 years without incient then
Predicted price = 776.811 - 46.273(3) = 637.992

If 10 years without incient then
Predicted price = 776.811 - 46.273(10) = 314.081

e) If 1.5 years without incient then
Predicted price = 776.811 - 46.273(1.5) = 707.4015

residual : 707.4015 - 700 = 7.4015

f) 1 - 0.9135 = 0.0865 = 8.65%

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