For item 1 to 4.The following data represent a set of 10experimental runs in whichtwo independent variables X1 and X2 are controlled andvalues of a response Yare observed:Y61.561.23252.531.522.55356.834.852.752.5355.23Estimate the multiple Linear regression, Y1. The regression estimate a.1.68X12400245025002700275028002900300031003200-0.04X254.556.443.265.245.547.56566.557.368=a + b₁X₁ + b₂ X2 Question 2The b1.1.68-1.0453.25-0.04Previous

Use the Excel and Perform the Regression. Followings are the Steps to perform the Regression 1) Open…

Answered: Estimate the multiple Linear…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

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Problem 1P

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Predict the average lifespan of an animal in years when the incubation/gestation time is 12 months. Animal: Nile crocodile, Aldabra giant tortoise, Lake sturgeon,Galápagos tortoise, Bowhead whale Average Lifespan (in Years):100 152 152 177 211 Incubation/ Gestation (in Months)3 8 0.25 4.7 regression equation and regression line if needed
The best predicted crash fatality rate for a year in which there are 475 metric tons of lemon imports is fatalities per 100,000 population. (Round to one decimal place as needed.)
Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed lemon/crash data, where lemon imports are in metric tons and the fatality rates are per 100,000 people, find the best predicted crash fatality rate for a year in which there are 475 metric tons of lemon imports. Is the prediction worthwhile? Lemon Imports Crash Fatality Rate 16 15.9 232 260 357 462 516 15.6 15.3 15 Find the equation of the regression line. (Round the constant three decimal places as needed. Round the coefficient to six decimal places as needed.)
The figure accompanying this exercise is a histogram of the residuals for a simple linear regression. Which condition(s) are verified in this figure? Be specific about which of the four necessary conditions are verified in this figure. (Select all that apply.) -2 -1 Residual O1. The form of the equation that links the mean value of y to x must be correct. 02. Observations in the sample are independent of each other. 03. For individuals in the population with the same particular value of x, the distribution of the values of y is a normal distribution with no outliers that influence the results unduly. 04. The standard deviation of the values of y from the mean y is the same regardless of the value of the x variable.
Find the regression equation, letting the first variable be the predictor (x) variable. Using the sh data, where lemon imports are in metric tons and the fatality rates are per te, ouple, find the best predicted crash fatality rate for a year in which there are 450 metric tons of lemon imports. Is the prediction worthwhile? Question Viewer Lemon Imports 228 264 362 498 Crash Fatality Rate 16.1 16 15.8 15.5 526 15.1 Find the equation of the regression line. ŷ=+x (Round the y-intercept to three decimal places as needed. Round the slope to four decimal places as needed.)
Fill in the blanks. a. Multicollinearity is considered to be severe if the VIF for one or more predictor variables is ______. or greater. b. If the coefficient of multiple determination for the regression of the predictor variable x11 on all the other predictor variables in a regression equation is 0.6, then the VIF for x1 is ______. c. The effect of multicollinearity in a polynomial regression analysis can be reduced by ______. the predictor variable.
The money raised and spent (both in millions of dollars) by all congressional campaigns for 8 recent 2-year periods are shown in the table. The equation of the regression line is y = 0.942x +27.609. Find the standard error of estimate s, and interpret the result. 793.9 1042.3 957.7 1203.3 450.7 673.7 745.1 778.6 Money raised, x Money spent, y 734.8 1024.2 929.1 1160.6 448.6 697.9 735.7 751.2 Find the standard error of estimate s, and interpret the result. (Round to three decimal places as needed.) How can the standard error of estimate be interpreted? O A. The standard error of estimate of the money raised for a specific amount of money spent is about s, million dollars. O B. The standard error of estimate of the money spent for a specific amount of money raised is about s, million dollars.
Find the value of regression
Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed lemon/crash data, where lemon imports are in metric tons and the fatality rates are per 100,000 people, find the best predicted crash fatality rate for a year in which there are 500 metric tons of lemon imports. Is the prediction worthwhile? Lemon Imports Crash Fatality Rate 15.9 15.7 225 261 357 492 529 O 14.9 15.3 15.4 Round the yntercept to three decimal places as needed. Round the stope to four decimal piaces as needed.) The best predicted crash fatality rate for a year in which there are 500 metric tons of lemon imports is fatalities per 100,000 population. (Round to one decimal place as needed.) Is the prediction worthwhile? O A. Since common sense suggests there should not be much of a relationship between the two variables, the prediction does not make much sense. O B. Since all of the requirements for finding the equation of the regression line are met, the prediction is…
Write the linear model to test the hypothesis that there is no treatment effect. Clearly describe each term in the model, and the range of the subscripts. Write the null hypothesis that you are testing. Call: lm(formula = score ~ list, data = hearing) Residuals: Min 1Q Median 3Q Max -14.7500 -5.5833 -0.2083 6.3333 16.4167 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 32.750 1.612 20.315 < 2e-16 *** listList2 -3.083 2.280 -1.352 0.17955 listList3 -7.500 2.280 -3.290 0.00142 ** listList4 -7.167 2.280 -3.144 0.00225 ** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 7.898 on 92 degrees of freedom Multiple R-squared: 0.1382, Adjusted R-squared: 0.1101 F-statistic: 4.919 on 3 and 92 DF, p-value: 0.00325
Based on data, check the linear regression for multicollinearity, and identify the best regression. Based on the final regression, check for autocorrelation of residuals, and make conclusion.
Compute the least-squares regression equation for the given data set. Round the slope and yFintercept to at least four decimal places. 4 y 7. 3. Send data to Excel Regression line equation: y =|

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Estimate the multiple Linear regression, Y = a + b₁X₁ + b2 X2 1. The regression estimate a. 52.53 55.23 1.68 68 -0.04