实验设计与分析（第6版，Montgomery著，傅珏生译) 第10章拟合回归模型10.9节思考题10.6 R语言解题
本文是实验设计与分析（第6版，Montgomery著，傅珏生译) 第10章拟合回归模型10.9节思考题10.6 R语言解题。主要涉及线性回归、回归的显著性。
10-6
vial <- seq(1, 6, 1)
Viscosity <- c(193,230,172,91,113,125)
Temperature <- c(1.6,15.5,22.0,43.0,33.0,40.0)
Catalyst <- c(851,816,1058,1201,1357,1115)
visc <- data.frame(vial, Viscosity, Temperature,Catalyst)
visc
lm.fit <- lm(Viscosity ~ Temperature+Catalyst, data=visc)
summary (lm.fit)
> summary (lm.fit)
Call:
lm.default(formula = Viscosity ~ Temperature + Catalyst, data = visc)
Residuals:
1 2 3 4 5 6
-24.987 24.307 11.820 -20.460 12.830 -3.511
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 350.99427 74.75307 4.695 0.0183 *
Temperature -1.27199 1.16914 -1.088 0.3562
Catalyst -0.15390 0.08953 -1.719 0.1841
---
Signif. codes:
0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 25.5 on 3 degrees of freedom
Multiple R-squared: 0.8618, Adjusted R-squared: 0.7696
F-statistic: 9.353 on 2 and 3 DF, p-value: 0.05138
summary (aov(lm.fit))
> summary (aov(lm.fit))
Df Sum Sq Mean Sq F value Pr(>F)
Temperature 1 10240 10240 15.751 0.0286 *
Catalyst 1 1921 1921 2.955 0.1841
Residuals 3 1950 650
---
Signif. codes:
0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
op <- par(mfrow=c(2,2), las=1)
plot(lm.fit)
par(op)
library(car)
carPlots(lm.fit)
