> pdf("F:\\sta4210\\CH03TA04.pdf")
> 
> plot(X,Y)
> 
> bank.reg1 <- lm(Y~X)
> summary(bank.reg1)

Call:
lm(formula = Y ~ X)

Residuals:
   Min     1Q Median     3Q    Max 
-59.23 -34.06  12.61  32.44  48.44 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)
(Intercept)  50.7225    39.3979   1.287     0.23
X             0.4867     0.2747   1.772     0.11

Residual standard error: 40.47 on 9 degrees of freedom
Multiple R-squared: 0.2586,     Adjusted R-squared: 0.1762 
F-statistic: 3.139 on 1 and 9 DF,  p-value: 0.1102 

> anova(bank.reg1)
Analysis of Variance Table

Response: Y
          Df  Sum Sq Mean Sq F value Pr(>F)
X          1  5141.3  5141.3  3.1389 0.1102
Residuals  9 14741.6  1638.0               
> 
> bank.aov1 <- lm(Y~factor(X))
> summary(bank.aov1)

Call:
lm(formula = Y ~ factor(X))

Residuals:
         1          2          3          4          5          6          7 
 5.000e+00 -1.200e+01  1.000e+01 -7.000e+00 -3.331e-15  1.600e+01  7.000e+00 
         8          9         10         11 
-1.600e+01 -5.000e+00 -1.000e+01  1.200e+01 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept)     35.00      10.71   3.267 0.022282 *  
factor(X)100    89.00      15.15   5.874 0.002030 ** 
factor(X)125   120.00      15.15   7.919 0.000517 ***
factor(X)150   117.00      18.56   6.305 0.001478 ** 
factor(X)175   105.00      15.15   6.930 0.000960 ***
factor(X)200    79.00      15.15   5.214 0.003428 ** 
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Residual standard error: 15.15 on 5 degrees of freedom
Multiple R-squared: 0.9423,     Adjusted R-squared: 0.8845 
F-statistic: 16.32 on 5 and 5 DF,  p-value: 0.004085 

> anova(bank.aov1)
Analysis of Variance Table

Response: Y
          Df Sum Sq Mean Sq F value   Pr(>F)   
factor(X)  5  18735  3747.0   16.32 0.004085 **
Residuals  5   1148   229.6                    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 
> 
> anova(bank.reg1,bank.aov1)
Analysis of Variance Table

Model 1: Y ~ X
Model 2: Y ~ factor(X)
  Res.Df   RSS Df Sum of Sq      F   Pr(>F)   
1      9 14742                                
2      5  1148  4     13594 14.801 0.005594 **
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 
>