Hawk thinks his heartrate will increase as he increases his skateboarding speed. To see if this relationship exists, he records six different speeds and models it with a scatterplot and regression output.Part A: Write the equation of the regression line using the regression output. Part B: What do the slope and intercept parameters mean using the context of the problem? Part C: Compute the margin of error that Hawk should use if he wants to provide a 99% confidence interval for the slope. Assume that conditions for inference are satisfied. 120110100908070609 9.5 10 10.5 11 11.5 12 12.5 13 13.5 14 14.5 15 15.5 16 16.5Speed, miles per hourRegression StatisticsMultiple R97.28153%R Square94.63696%Adjusted R Square 93.29620%Standard Error4.806846736Observations6Pulse, beats per minute dfSSMSFRegression 1 1,630.910231 1,630.910231 70.58453Residual4 92.42310217 23.10577554Total5 1,723.333333Coefficients Standard Errort Statp-ValueIntercept 1.301246992 10.660366510.1220640010.908735Speed7.315685846 0.870763656 8.401459797 0.001098

Solution: Given information: n= 6 observation k= 1 independent variable α=0.01 Level of…

Answered: Hawk thinks his heartrate will increase…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Question

Hawk thinks his heartrate will increase as he increases his skateboarding speed. To see if this relationship exists, he records six different speeds and models it with a scatterplot and regression output.

Part A: Write the equation of the regression line using the regression output.

Part B: What do the slope and intercept parameters mean using the context of the problem?

Part C: Compute the margin of error that Hawk should use if he wants to provide a 99% confidence interval for the slope. Assume that conditions for inference are satisfied.

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9 9.5 10 10.5 11 11.5 12 12.5 13 13.5 14 14.5 15 15.5 16 16.5
Speed, miles per hour
Regression Statistics
Multiple R
97.28153%
R Square
94.63696%
Adjusted R Square 93.29620%
Standard Error
4.806846736
Observations
6
Pulse, beats per minute

df
SS
MS
F
Regression 1 1,630.910231 1,630.910231 70.58453
Residual
4 92.42310217 23.10577554
Total
5 1,723.333333
Coefficients Standard Error
t Stat
p-Value
Intercept 1.301246992 10.66036651
0.1220640010.908735
Speed
7.315685846 0.870763656 8.401459797 0.001098

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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