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Call:
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lm(formula = y ~ x)
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Residuals:
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1 2 3 4 5 6
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3.3333 -0.6667 -2.6667 -2.6667 -0.6667 3.3333
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Coefficients:
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Estimate Std. Error t value Pr(>|t|)
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(Intercept) -9.3333 2.8441 -3.282 0.030453 *
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x 7.0000 0.7303 9.585 0.000662 ***
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---
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Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
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Residual standard error: 3.055 on 4 degrees of freedom
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Multiple R-squared: 0.9583, Adjusted R-squared: 0.9478
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F-statistic: 91.88 on 1 and 4 DF, p-value: 0.000662
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> par(mfrow=c(2, 2)) # Request 2x2 plot layout
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> plot(lm_1) # Diagnostic plot of regression model
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