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y <- c (32, 36, 27, 34, 28, 29, 39, 29, 28, 26, 38, 39)
X1 <-c(57, 59, 49, 62, 51, 50, 55, 48, 42, 42, 61, 57)
X2 <- c(8, 10, 6, 11, 8, 7, 10, 9, 10, 6, 12, 9)
length(y)
## [1] 12
length(X1)
## [1] 12
length(X2)
## [1] 12
g <- lm(y ~ X1 + X2)
summary(g)
##
## Call:
## lm(formula = y ~ X1 + X2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.9166 -1.1626 -0.4743 0.4228 4.9709
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.9393 6.8470 0.283 0.7834
## X1 0.4231 0.1632 2.593 0.0291 *
## X2 0.8861 0.5863 1.511 0.1650
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.915 on 9 degrees of freedom
## Multiple R-squared: 0.7113, Adjusted R-squared: 0.6471
## F-statistic: 11.09 on 2 and 9 DF, p-value: 0.003733
anova(g)
## Analysis of Variance Table
##
## Response: y
## Df Sum Sq Mean Sq F value Pr(>F)
## X1 1 169.025 169.025 19.8898 0.001578 **
## X2 1 19.409 19.409 2.2839 0.165005
## Residuals 9 76.483 8.498
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1