> tapply(peak_y,susp_xf,mean)
    99.9    125.3    150.2    174.9 
102.8017 110.6100 118.3333 126.6950 
> tapply(peak_y,susp_xf,sd)
     99.9     125.3     150.2     174.9 
0.4326854 0.6369615 0.9066569 0.7038963 
> 
> stdin.mod1 <- aov(peak_y~susp_xf)
> summary.lm(stdin.mod1)

Call:
aov(formula = peak_y ~ susp_xf)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.94333 -0.53042  0.05083  0.49083  1.12667 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept) 114.6100     0.1411 812.442   <2e-16 ***
susp_xf.L    17.7551     0.2821  62.931   <2e-16 ***
susp_xf.Q     0.2767     0.2821   0.981    0.338    
susp_xf.C     0.1617     0.2821   0.573    0.573    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.6911 on 20 degrees of freedom
Multiple R-squared:  0.995,     Adjusted R-squared:  0.9942 
F-statistic:  1321 on 3 and 20 DF,  p-value: < 2.2e-16

> anova(stdin.mod1)
Analysis of Variance Table

Response: peak_y
          Df  Sum Sq Mean Sq F value    Pr(>F)    
susp_xf    3 1892.08  630.69  1320.5 < 2.2e-16 ***
Residuals 20    9.55    0.48                      
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> 
> contrasts(susp_xf) <-
+ cbind(c(-.674207,-.219665,.2259286,.6679435),
+       c(.4978482,-.507638,-.492299,.5020885),
+       c(-.218157,.6663716,-.67572,.2275052))
> 
> stdin.mod2 <- aov(peak_y~susp_xf)
> summary.lm(stdin.mod2)

Call:
aov(formula = peak_y ~ susp_xf)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.94333 -0.53042  0.05083  0.49083  1.12667 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept) 114.6100     0.1411 812.442   <2e-16 ***
susp_xf1     17.7532     0.2821  62.924   <2e-16 ***
susp_xf2      0.3865     0.2821   1.370    0.186    
susp_xf3      0.1440     0.2821   0.511    0.615    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.6911 on 20 degrees of freedom
Multiple R-squared:  0.995,     Adjusted R-squared:  0.9942 
F-statistic:  1321 on 3 and 20 DF,  p-value: < 2.2e-16

> anova(stdin.mod2)
Analysis of Variance Table

Response: peak_y
          Df  Sum Sq Mean Sq F value    Pr(>F)    
susp_xf    3 1892.08  630.69  1320.5 < 2.2e-16 ***
Residuals 20    9.55    0.48                      
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>