Regression-anova-1.R

x<-c(0.02,0.07,0.11,0.15)
y<-c(242,237,231,201)
model1<-lm(y~x)
summary(model1)

## 
## Call:
## lm(formula = y ~ x)
## 
## Residuals:
##      1      2      3      4 
## -5.563  4.113  9.854 -8.404 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)   
## (Intercept)   253.43      10.77  23.537   0.0018 **
## x            -293.53     107.81  -2.723   0.1126   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 10.38 on 2 degrees of freedom
## Multiple R-squared:  0.7875, Adjusted R-squared:  0.6813 
## F-statistic: 7.413 on 1 and 2 DF,  p-value: 0.1126

anova(model1)

## Analysis of Variance Table
## 
## Response: y
##           Df Sum Sq Mean Sq F value Pr(>F)
## x          1 799.14  799.14  7.4127 0.1126
## Residuals  2 215.61  107.81