The horsepower (Y, in bhp) of a motor car engine was measured at a chosen set of values of running speed (X, in rpm). The data are given below (the first row is the running speed in rpm and the second row is the horsepower in bhp): rpm 1100 1400 1700 2300 2700 3200 3500 4000 4600 5200 5600 6100 Horsepower (bhp) 50.2 64.29 67.83 98.56 131.09 163.65 161.55 198.62 226.03 254.71 283.63 299.81 The mean and sum of squares of the rpm are 3450.00003450.0000 rpm and 173900000.0000 rpm^2 respectively; the mean of the hor

Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter7: Analytic Trigonometry
Section7.6: The Inverse Trigonometric Functions
Problem 94E
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The horsepower (Y, in bhp) of a motor car engine was measured at a chosen set of values of running speed (X, in rpm). The data are given below (the first row is the running speed in rpm and the second row is the horsepower in bhp):

rpm 1100 1400 1700 2300 2700 3200 3500 4000 4600 5200 5600 6100
Horsepower (bhp) 50.2 64.29 67.83 98.56 131.09 163.65 161.55 198.62 226.03 254.71 283.63 299.81

The mean and sum of squares of the rpm are 3450.00003450.0000 rpm and 173900000.0000 rpm^2 respectively; the mean of the horsepower values is 166.6642 bhp and the sum of the products of the two variables is 8506152.0000 rpm bhp.

With a slope of 0.052 and an intercept of -11.694 calculate the following please.

Note: For sub-parts below, use the slope and intercept values in Part a, corrected to 3 decimal places to calculate answers by hand using a scientific calculator.

Part b)

Based on the regression model, what level of horsepower would you expect the engine to produce if running at 2400 rpm?

Answer: 

Part c)

Assuming the model you have fitted, if increase the running speed by 100 rpm, what would you expect the change in horsepower to be?

Answer: 

Part d)

The standard error of the estimate of the slope coefficient was found to be 0.001160. Provide a 95% confidence interval for the true underlying slope.

Confidence interval: (  ,  )

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