Use the given equation of the least squares regressionline to predict the output when x is 5. Round the finalvalues to three places, if necessary.(2, 13), (4, 11), (5, 7)y = 17.143-1.857xFind the predicted output when x is 5:choose your answer...

The following information has been given: The estimated regression line is given as :…

Answered: Use the given equation of the least…

Elementary Linear Algebra (MindTap Course List)

8th Edition

ISBN:9781305658004

Author:Ron Larson

Publisher:Ron Larson

Chapter5: Inner Product Spaces

Section5.CR: Review Exercises

Problem 62CR

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The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.
Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
Find the slope m for the least-squares regression line. x y 5 8 9 10 11 13 17 19
The following data is given: x -7 -4 -1 0 2 5 7 y 20 14 5 3 -2 -10 -15 Use linear least-squares regression to determine the coefficients m and b in the function y=mx+b that best fit the data.
Which of the following are feasible equations of a least squares regression line for the change in a millionaire's bank account balance? Select all that apply. Select all that apply: yˆ=75,000+4400x yˆ=75,000−4400x yˆ=−75,000+4400x yˆ=−75,000−4400x
According to the summary result of linear regression model between A and B obtained from R given below, we can fit a regression line. Assume thatA has any value. If we decrease the value of A by 3, how would Y be affected?a) 58.8945 decreaseb) 58.8945 increasec) 29.8827 increased) 49.5142 decreasee) 29.8827 decrease
a)Find the equation of the least-squares regression line for the data. (Where x is the independent variable.) Round constants to the nearest hundredth. b)Use the equation from part (a) to determine, to the nearest centimeter, the projected wingspan of a pterosaur if its humerus is 53 centimeters.
Which of the following are feasible equations of a least squares regression line for the annual population change of a small country since the year 2000? Select all that apply. Select all that apply: A. yˆ=38,000+2500x B. yˆ=38,000−2500x C. yˆ=−38,000+2500x D. yˆ=−38,000−2500x
Suppose Wesley is a marine biologist who is interested in the relationship between the age and the size of male Dungeness crabs. Wesley collects data on 1,000 crabs and uses the data to develop the following least-squares regression line where ?X is the age of the crab in months and ?ˆY^ is the predicted value of ?Y, the size of the male crab in cm. ?ˆ=8.2052+0.5693?Y^=8.2052+0.5693X What is the value of ?ˆY^ when a male crab is 21.7865 months old? Provide your answer with precision to two decimal places. ?ˆ= Interpret the value of ?ˆ. The value of ?ˆ is the predicted number of crabs out of the 1,000 crabs collected that will be 21.7865 months old. the probability that a crab will be 21.7865 months old. the predicted size of a crab when it is 21.7865 months old. the predicted incremental increase in size for every increase in age by 21.7865 months.
Compute the least-squares regression equation for the given data set. Round the slope and y-intercept to at least four decimal places. 2 4 7 6 6 5 3 3 4 2
The following data is given... x 1 2 3 5 8 y 0.8 1.9 2.2 3 3.5 Determine the coefficients m and b in the function y=[m√x+b]1/2 that best fit the data. Write the equation in a linear form, and use linear least-squares regression to determine the value of the coefficients.
Suppose Wesley is a marine biologist who is interested in the relationship between the age and the size of male Dungeness crabs. Wesley collects data on 1,000 crabs and uses the data to develop the following least-squares regression line where ? is the age of the crab in months and ?ˆ is the predicted value of ?, the size of the male crab in cm. ?ˆ=8.1312+0.5226? What is the value of ?ˆ when a male crab is 23.0736 months old? Provide your answer with precision to two decimal places. ?ˆ = Interpret the value of ?. The value of ?ˆis the predicted size of a crab when it is 23.0736 months old. the predicted incremental increase in size for every increase in age by 23.0736 months. the predicted number of crabs out of the 1,000 crabs collected that will be 23.0736 months old. the probability that a crab will be 23.0736 months old.

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Use the given equation of the least squares regression line to predict the output when x is 5. Round the final values to three places, if necessary. (2, 13), (4, 11), (5, 7) y = 17.143-1.857x Find the predicted output when x is 5: choose your answer...