Estimate the multiple Linear regression, Y = a + b₁X₁ + b2 X2 1. The regression estimate a. 52.53 55.23 1.68 68 -0.04
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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 neededThe 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.)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.Perform a linear regression analysis on the following data and determine the "a" coefficient (i.e., slope): Y 4.99 22.19 1.96 9.89 2.98 11 9 40.46 4.04 18.93 6.06 25 0.88 0.19 8.02 34.02 6.97 28.03
- Find the value of regressionFind the regression equation, letting the first variable be the predictor (x) variable. Find the best predicted Nobel Laureate rate for a country that has 79.4 Internet users per 100 people. How does it compare to the country's actual Nobel Laureate rate of 1.2 per 10 million people? Internet Users Per 100 Nobel Laureates 79.3 5.6 80.5 24.2 78.8 8.7 45.2 0.1 82.5 6.2 38 0.1 90.3 25.4 88.6 7.6 80.3 9.1 83.1 12.6 53.3 1.9 76.3 12.7 56.6 3.3 78.5 1.5 91.6 11.5 93.4 25.2 65.3 3.1 57.3 1.9 68.2 1.7 94.8 31.6 85.4 31.3 86.4 19.1 78.3 10.9 2) Check ImageFind 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: 0.00325Based 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.