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Brawn versus brain How is the weight of an animal’s brain related to the weight of its body? Researchers collected data on the brain weight (in grams) and body weight (in Page Number: 813 Page Number: 814 kilograms) for 96species of mammals. The following figure is a scatterplot of the logarithm of brain weight against the logarithm of body weight for all 96species. The least-squares regression line for the transformed data is

logy=1.01+0.72logxlogy^=1.01+0.72logx

Based on footprints and some other sketchy evidence, some people believe that a large ape-like animal, called Sasquatch or Bigfoot, lives in the Pacific Northwest. Bigfoot’s weight is estimated to be about 127kilograms (kg). How big do you expect Bigfoot’s brain to be?

Short Answer

Expert verified

The expected brain weight is 334.734grams.

Step by step solution

01

Given Information

Given data:

02

Explanation

Substituting the value of xin the regression equation

logy=1.01+0.72log(127)

=2.5247

Taking each side of the result's exponential with a base of 10:

y=10logy

=102.5247

=334.734

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Most popular questions from this chapter

If P(A)=0.24and P(B)=0.52and events Aand Bare independent, what is P(Aor B)?

а. 0.1248

b. 0.28

c. 0.6352

d.0.76

e. The answer cannot be determined from the given information.

The swinging pendulum Refer to Exercise 33. We took the logarithm (base 10) of the values for both length and period. Here is some computer output from a linear regression analysis of the transformed data.


a. Based on the output, explain why it would be reasonable to use a power model to describe the relationship between the length and period of a pendulum.

b. Give the equation of the least-squares regression line. Be sure to define any variables you use.

c. Use the model from part (b) to predict the period of a pendulum with a length of 80cm.

Each morning, coffee is brewed in the school workroom by one of three faculty members, depending on who arrives first at work. Mr. Worcester arrives first 10% of the time, Dr. Currier arrives first 50%of the time, and Mr. Legacy arrives first on the remaining mornings. The probability that the coffee is strong when brewed by Dr. Currier is 0.1, while the corresponding probabilities when it is brewed by Mr. Legacy and Mr. Worcester are 0.2 and 0.3, respectively. Mr. Worcester likes strong coffee!
(a) What is the probability that on a randomly selected morning the coffee will be strong?
(b) If the coffee is strong on a randomly selected morning, what is the probability that it was brewed by Dr. Currier?

Exercises T12.4–T12.8 refer to the following setting. An old saying in golf is “You drive for show and you putt for dough.” The point is that good putting is more important than long driving for shooting low scores and hence winning money. To see if this is the case, data from a random sample of 69 of the nearly 1000 players on the PGA Tour’s world money list are examined. The average number of putts per hole (fewer is better) and the player’s total winnings for the previous season are recorded and a least-squares regression line was fitted to the data. Assume the conditions for
inference about the slope are met. Here is computer output from the regression analysis:

T12.6 The P -value for the test in Exercise T12.5 is 0.0087. Which of the following is a correct interpretation of this result?
a. The probability there is no linear relationship between average number of putts per hole and total winnings for these 69 players is 0.0087.
b. The probability there is no linear relationship between average number of putts per hole and total winnings for all players on the PGA Tour’s world money list is 0.0087.
c. If there is no linear relationship between average number of putts per hole and total winnings for the players in the sample, the probability of getting a random sample of 69 players that yields a least-squares regression line with a slope of −4,139,198 or less is 0.0087.
d. If there is no linear relationship between average number of putts per hole and total winnings for the players on the PGA Tour’s world money list, the probability of getting a random sample of 69 players that yields a least-squares regression line with a slope of −4,139,198 or less is 0.0087.
e. The probability of making a Type I error is 0.0087.

Multiple Choice Select the best answer for Exercises 23-28. Exercises 23-28 refer to the following setting. To see if students with longer feet tend to be taller, a random sample of 25students was selected from a large high school. For each student, x=foot length and y=height were recorded. We checked that the conditions for inference about the slope of the population regression line are met. Here is a portion of the computer output from a least-squares regression analysis using these data:

Which of the following is the equation of the least-squares regression line for predicting height from foot length?

a. height^=10.2204+0.4117(foot length) height^=10.2204+0.4117(foot length)

b.height^=0.4117+3.0867 (foot length) height^=0.4117+3.0867(foot length)

c. height^=91.9766+3.0867(foot length) height^=91.9766+3.0867(foot length)

d. height^=91.9766+6.47044 (foot length)height^=91.9766+6.47044(foot length)

e. height^=3.0867+6.47044(foot length)heiight^=3.0867+6.47044(foot length)

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