Q3: Multiple regression using Minitab. interpret the results inbullets step by stepRegression Analysis: y versus x1, x2Regression Equationy 18.4+ 2.010 x1 + 4. 738 x2CoefficientsTermConstantx1x2Model SummaryCoef-18.42.0104.738S12. 7096Analysis of Variance1R-sq92.55%SE Coef18.00.2470.948+T-Value-1.028. 135.00R-sq(adj)90.42%Source DF Adj SS Adj MS F-Value P-ValueRegression 2 14052 7026.1 43.500.000x1110689 10688.7 66.170.000x240314030,924.950.002P-Value VIF0.3410.000 1.000.0021.00R-sq(pred)87.95%+5 ErrorTotal711319 15183161.5

Given thatDependent variable: yIndependent variables: x1 and x2

Answered: Q3: Multiple regression using Minitab.…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

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Multiple regression analysis was used to study how an individual's income (Y in thousands of dollars) is influenced by age (X1 in years), level of education (X2 ranging from 1 to 5), and the person's gender (X3 where 0 =female and 1=male). The following is a partial result of computer output that was used on a sample of 20 individuals. Present the estimated regression equation and compute the coefficient of determination. Explain it. Use the t test to determine the significance of each independent variable. Let α = 0.05. (For each test, give the null and alternative hypotheses, test statistic, and conclusion.) Use the F test to determine whether or not the regression model is significant. Let α = 0.05. (For the test, give the null and alternative hypotheses, test statistic, and conclusion.) Does the estimated regression equation provide a good fit for the observed data? Explain it. Suppose a new person with X1=40, X2=4, X3=0. Use the estimated regression equation in part (a)…
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The equation used to predict annual cauliflower yield (in pounds per acre) is y=24,596+4.423x1−4.772x2, where x1 is the number of acres planted an x2 is the number of acres harvested. Use the multiple regression equation to predict the y-values for the values of the independent variables.
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The age and height (in cm) of 400 adult women from Bolivia were measured. A researcher wants to know if age has any effect on height. A linear regression is carried out in Minitab and the following output obtained. Coefficients Term Constant Age (a) Write down the regression model. (b) Interpret the regression coefficient for the fitted model. (c) Use the output from Minitab to explain if the age of a participant affects their height. Percent (d) The normal probability plot of the residuals from this regression model is given below. Do the assumptions of the regression model seem reasonable? Justify your answer. 99.9 8 28 22299229 88 Coef SE Coef 152.94 7.69 0.022 0.231 01 -100 T-Value P-Value VIF 19.90 0.000 0.10 0.924 1.00 -50 Normal Probability Plot (response is Height) 0 Residual 50 ***** 100 150
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What is the answer to part d

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Q3: Multiple regression using Minitab. interpret the results in bullets step by step Regression Analysis: y versus x1, x2 Regression Equation