• Your student ID # ie 212

• the R code for the data generation; the value of the error variance s used(re

to your ID#)

• the generated dataset (in appendix)

• R code for analysis

• detailed interpretation of the results

- Thread starter noormohid
- Start date

• Your student ID # ie 212

• the R code for the data generation; the value of the error variance s used(re

to your ID#)

• the generated dataset (in appendix)

• R code for analysis

• detailed interpretation of the results

> x = rnorm(30,0,1)

> y = rnorm(30,0,1)

> y = 32+ 11*x + rnorm(30,0,3.815786)> plot(x,y)

> asd= lm(y~x)

> summary(asd)

Call:

lm(formula = y ~ x)

Residuals:

Min 1Q Median 3Q Max

-9.163 -2.430 -0.205 2.390 9.227

Coefficients:

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

(Intercept) 31.2287 0.7511 41.58 < 2e-16 ***x

10.9577 0.8386 13.07 1.95e-13 ***---

Signif. codes:

0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 3.949 on 28 degrees of freedomMultiple R-squared: 0.8591, Adjusted R-squared: 0.8541 F-statistic: 170.7 on 1 and 28 DF, p-value: 1.948e-13

> plot(asd)

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