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Consider the following example of a simple linear regression in R. x = c(-1,0,1) y = c(0,4,2) lm(yx) ## Call: ## lm(formula = y ~ x) ## Coefficients: # (Intercept) 2 Please write down the design matrix X and compute the values of the slope in the R output (make sure you show the details). Please interpret both intercept and slope in the simple linear regression

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R RGui (64-bit) File Edit Packages岦indows Help R Untitled- R Editor R R Console y-C(o,4,2) X-as.matrix (cbind (rep (1,3) , x)) y- (0,4,2) X-as.matrix (ebind (rep (1,3), x) beta-solve (t (X) beta beta > *EX) *%t(X)s*ty I,1 Activate Windows Go to Settings to activate Windows 4) ENG 10t41 AMThe Simp ney egressi en modlel Can be WviHen au, -I 2. 2 Nao model can be WeiHen as, в,--the intercept is the expected mean value of y w hen all x:0. One Unit increate in 9he predictor va iable the oudtuome va rłable InCYe hell be increa ơe h po unit

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