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Based on the residual plot, do you expect your prediction to be too high or too low? Justify your answer.

Short Answer

Expert verified

Our predictions will be too low.

Step by step solution

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Given Information

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Explanation

Based on the residual plot given in this question we can say that the points are first increasing and then it start decreasing in the year ahead. Thus, in the year 1890, we expected the prediction to be too low as the last point in the residual plot is too low so our prediction will be if the same trend follows.

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Most popular questions from this chapter

Random assignment is part of a well-designed comparative experiment because

(a) It is more fair to the subjects.

(b) It helps create roughly equivalent groups before treatments are imposed on the subjects.

(c) It allows researchers to generalize the results of their experiment to a larger population.

(d) It helps eliminate any possibility of bias in the experiment.

(e) It prevents the placebo effect from occurring

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Based on footprints and some other sketchy evidence, some people think that a large apelike animal, called Sasquatch or Bigfoot, lives in the Pacific Northwest. His weight is estimated to be about 280pounds, or 127kilograms. How big is Bigfootโ€™s brain? Show your method clearly

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Prey attracts predators Here is one way in which nature regulates the size of animal populations: high population density attracts predators, which remove a higher proportion of the population than when the density of the prey is low. One study looked at kelp perch and their common predator, the kelp bass. The researcher set up four large circular pens on sandy ocean bottoms off the coast of southern California. He chose young perch at random from a large group and placed 10,20,40 and60 perch in the four pens. Then he dropped the nets protecting the pens, allowing the bass to swarm in, and counted the perch left after two hours. Here are data on the proportions of perch eaten in four repetitions of this setup .

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We used Minitab software to carry out a least-squares regression analysis for these data. A residual plot and a histogram of the residuals are shown below. Check whether the conditions for performing inference about the regression model are met.

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