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Using R program (1) Use the comman: data(stackloss) to load the stackloss data,

ID: 3050838 • Letter: U

Question

Using R program (1) Use the comman: data(stackloss) to load the stackloss data, answer the following questions: (a) Fit a multiple regression model to predict stackloss from the other three variables. And summarize the results (b) Construct 95% confidence intervals for the coefficients of all the coefficients in (a), note: in the class I told you the degrees of freedom is (n-p-1), so when you use t distri- bution, do not forget the dof. (c) For the coefficient of airflow, what is the p-value and what is the conclusion?

Explanation / Answer

#a)

> data(stackloss)

> s=stackloss

> X1=s[,1]

> X2=s[,2]

> X3=s[,3]

> Y=s[,4]

> reg=lm(Y~X1+X2+X3)

> reg

Call:

lm(formula = Y ~ X1 + X2 + X3)

Coefficients:

(Intercept)           X1           X2           X3

   -39.9197       0.7156       1.2953      -0.1521

> z=summary(reg)

> z

Call:

lm(formula = Y ~ X1 + X2 + X3)

Residuals:

    Min      1Q Median      3Q     Max

-7.2377 -1.7117 -0.4551 2.3614 5.6978

Coefficients:

            Estimate Std. Error t value Pr(>|t|)   

(Intercept) -39.9197    11.8960 -3.356 0.00375 **

X1            0.7156     0.1349   5.307 5.8e-05 ***

X2            1.2953     0.3680   3.520 0.00263 **

X3           -0.1521     0.1563 -0.973 0.34405   

---

Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 3.243 on 17 degrees of freedom

Multiple R-squared: 0.9136,    Adjusted R-squared: 0.8983

F-statistic: 59.9 on 3 and 17 DF, p-value: 3.016e-09

INTERPRETATION: here dataset contain 91% variation.

> #b)

> confint(reg,'X1',level=0.95)

       2.5 %   97.5 %

X1 0.4311143 1.000166

> confint(reg,'X2',level=0.95)

       2.5 %   97.5 %

X2 0.5188228 2.071749

> confint(reg,'X3',level=0.95)

        2.5 %    97.5 %

X3 -0.4818741 0.1776291

> #c)

> a=z$coefficients

> pvalue=a[,4]

> pvalue[2]

          X1

5.799025e-05

INTERPRETATION: P-value for coefficient of airflow is 5.799025e-05 is less than 0.05 hence we conclude that the variable airflow is statistically significant at common level alpha i.e 0.05.

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