2.2. The analyst created plots that have the following shapes. Below for example, the first plot issimply fitting a regression with say only bacteria B and its growth rate and the second plot is aresidual plot.بتنی برŶ-1.82 + .0435XHe then realises that a multiple regression of the first order will not fit the data appropriately.2.2.1. Provide the regression model, the regression function and the estimator (response function)for the model that he should use to fit the data. Provide the name of such a regression modeland point out the problems that can arise with these types of regression models. [Do notforget to centre]

Given information: The scatterplot and residual plot are given.

Answered: The analyst created plots that have the…

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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Briefly describe what is meant by the problem of errors in measurement of the predictor variables and describe its effect on a regression analysis.
Stoaches are fictional creatures that nest in truffula forests. A researcher wants to know whether there is a relationship between a stoach’s wingspan (?W, the predictor) and its nest height (?H, the response). A sample of 85 stoaches is observed, and for each, the wing-span (in cm) and the nest height (in m) are recorded. The observed data meet the assumptions for a linear regression, so the researcher fits the regression model and obtains a regression equation ℎ̂=−4.273+0.834?,h^=−4.273+0.834w, with standard error for the coefficient of ?w equal to 0.242. Determine the ?p-value from a test for a statistically significant linear dependence of nest height on wing-span. (Give your answer to 4 decimal places.
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The police chief believes that maintenance costs on high-mileage police vehicles are much higher than those costs for low-mileage vehicles. If high-mileage vehicles are costing too much, it may be more economical to purchase more vehicles. An analyst in the department regresses yearly maintenance costs (Y) for a sample of 200 police vehicles on each vehicle’s total mileage for the year (X). The regression equation finds: Y = $50 + .030X with a r2 of .90 If a vehicle’s mileage for the year is 50,000, what is its predicted maintenance costs? What does an r2 of .90 tell us? Is this a strong or weak correlation? How can you tell?

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The analyst created plots that have the following shapes. Below for example, the first plot is simply fitting a regression with say only bacteria B and its growth rate and the second plot is residual plot.