can you please help me solve sub-parts e, f, g A random sample of 20 observations from iris species versicolor was obtained todetermine the association between sepal length (cm) and sepal width (cm). The collecteddata are presented below:length (x): 7.0 6.4 6.9 5.5 6.5 5.7 6.3 4.9 6.6 5.2 5.0 5.9 6.0 6.1 5.6 6.7 5.6 5.8 6.2 5.6width (y): 3.2 3.2 3.1 2.3 2.8 2.8 3.3 2.4 2.9 2.7 2.0 3.0 2.2 2.9 2.9 3.1 3.0 2.7 2.2 2.5a)* Obtain an appropriate graph to display the data. Does a simple linear regression modelappear to be an appropriate model? Explain.T = 5.975, j = 2.76, E-1X;Yi =155.06,332.51, Σ1 - 720.93, ΣSSE = 1.66b) Calculate the least squares estimates for the regression coefficients andprovide the fitted regression equation.c) Interpret the estimated regression coefficients.d) Calculate the least squares estimate for o².e)* Does a linear regression function appear to give a good fit here? Compareand contrast with the following iris setosa data set. Which model do youthink will yield more accurate predictions? Explain.length (x) : 5.1 4.9 4.7 4.6 5.0 5.4 4.6 5.0 4.4 4.9 5.4 4.8 4.8 4.3 5.8 5.7 5.4 5.1 5.7 5.1width (y): 3.5 3.0 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 3.7 3.4 3.0 3.0 4.0 4.4 3.9 3.5 3.8 3.8Obtain a point estimates for both models of the mean sepal width whensepal length3.7.g) Obtain a point estimates for both models of the change in mean of sepalwidth when sepal length grows by 1 cm.

Name: can you please help me solve sub-parts e, f, g A random sample of 20 o
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Description: can you please help me solve sub-parts e, f, g A random sample of 20 observations from iris species versicolor was obtained todetermine the association between sepal length (cm) and sepal width (cm). The collecteddata are presented below:length (x):

e) The linear regression equation in the first data is; Width = 1.214 + 0.259 * Length The…

Math

Statistics

e)* Does a linear regression function appear to give a good fit here? Compare and contrast with the following iris setosa data set. Which model do you think will yield more accurate predictions? Explain. length (x): 5.1 4.9 4.7 4.6 5.0 5.4 4.6 5.0 4.4 4.9 5.4 4.8 4.8 4.3 5.8 5.7 5.4 5.1 5.7 5.1 width (y): 3.5 3.0 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 3.7 3.4 3.0 3.0 4.0 4.4 3.9 3.5 3.8 3.8 f) Obtain a point estimates for both models of the mean sepal width when sepal length = 3.7. g) Obtain a point estimates for both models of the change in mean of sepal width when sepal length grows by 1 cm.

e)* Does a linear regression function appear to give a good fit here? Compare and contrast with the following iris setosa data set. Which model do you think will yield more accurate predictions? Explain. length (x): 5.1 4.9 4.7 4.6 5.0 5.4 4.6 5.0 4.4 4.9 5.4 4.8 4.8 4.3 5.8 5.7 5.4 5.1 5.7 5.1 width (y): 3.5 3.0 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 3.7 3.4 3.0 3.0 4.0 4.4 3.9 3.5 3.8 3.8 f) Obtain a point estimates for both models of the mean sepal width when sepal length = 3.7. g) Obtain a point estimates for both models of the change in mean of sepal width when sepal length grows by 1 cm.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter10: Statistics

Section10.6: Summarizing Categorical Data

Problem 32PPS

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