(e) Interpret the slope coefficients that you deemed significant in the expected direction. Does the y-intercept estimate have a logical interpretation this time? If yes, what is it? If not, why not? d)The Null and Alternative hypotheses for income coefficient as follows:Null hypotheses, Ho: B₁=0Alternative hypotheses, H: B₁ #0aFrom the output, observe that the test statistic value for income coefficient is 8.369The p value is 0.0000The level of significance is, α = 0.01Compare the p value with the level of significance.Here, the p value is less than the level of significance, so reject the Null hypotheses.Hence, conclude that the slope coefficient for income variable is significant.The Null and Alternative hypotheses for Size coefficient as follows:Null hypotheses, H: ₂ = 0Alternative hypotheses, H: B₂ #0From the output, observe that the test statistic value for income coefficient is 10.895The p value is 0.0000The level of significance is, α = 0.01Compare the p value with the level of significance.Here, the p value is less than the level of significance, so reject the Null hypotheses.Hence, conclude that the slope coefficient for size variable is significant.e)If increasing every one household in size, then the annual credit card charge will also beincreases by 380.176 dollars when the income variable is treated as constant.If increasing every one dollar in income, then the annual credit card charge will alsoincreases by 32.881 dollars when size variable is treated as constant.Yes.There is some logical interpretation in this time for y intercept, because the averageannual credit card charges is not 1257.003 when size and income variables are treated asconstants.This is not logical for this model.I > Income <- c(4016, 3159, 5100, 4742, 1864, 4070, 2731, 3348, 4764, 5573, 2583, 3866, 3586, 5037, 3605, 5345, 5370$>Credit <-c(4016, 3159, 5100, 4742, 1864, 4070, 2731, 3348, 4764, 5573, 2583, 3866, 3586, 5037, 3605, 5345, 5370$> Size <- c(3, 2, 4, 5, 2, 2, 1, 2, 4, 6, 1, 2, 5, 4, 2, 5, 6, 2, 3, 3, 4, 1, 2, 3, 4, 6, 2, 1, 5, 6, 3, 6, 2, 5, $> Income <- c(54, 30, 32, 50, 31, 55, 37, 40, 66, 54, 30, 48, 34, 67, 50, 67, 55, 52, 51, 25, 48, 27, 33, 65, 63, $> model <- 1m (Credit Income + Size)> summary (model)Call:1m (formula Credit Income + Size)Residuals:Min1QMedian3QMax1270.10-1172.67 -169.4415.63 161.81Coefficients:Estimate Std. Errort value Pr (>1t|)(Intercept) 1257.003 197.279 6.372 7.35e-08Income3.929 8.369 7.20e-11***34.894 10.895 1.87e-14 ***32.881380.176SizeSignif. codes: 0.***** 0.001 *** 0.01 0.05 0.11Residual standard error: 393.8 on 47 degrees of freedomMultiple R-squared: 0.8293,Adjusted R-squared: 0.822F-statistic: 114.2 on 2 and 47 DF, p-value: < 2.2e-16a)From the output, observe that the regression equation as follows:y=1257.003+32.881x Income +380.176x Sizeb)b)From the output, observe that the adjusted coefficient of determination value is 0.5945This value indicates that how the model is likely to be useful in predicting the annualcredit card changes.The model is most likely to be useful, because this value is high value.c)The null and alternative hypotheses as follows:Null hypotheses, Ho: the overall regression model is not significant.Alternative hypotheses, H: the overall regression model is significant.From the output, observe that F statistic is 114.2The p value is approximately 0.0000The level of significance is, α = 0.01Compare the p value with the level of significaHere, the p value is less than the level of significance, so reject the Null hypotheses.Hence, conclude that the overall regression model is significant.

Regression equation comprising more than one factor is called multiple regression equation.

Answered: Interpret the slope coefficients that…

Interpret the slope coefficients that you deemed significant in the expected direction. Does the y-intercept estimate have a logical interpretation this time? If yes, what is it? If not, why not?

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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