Yields from a Barley Field Trial

The immer data frame has 30 rows and 4 columns. Five varieties of barley were grown in six locations in each of 1931 and 1932.

immer

Format

This data frame contains the following columns:

Loc

The location.

Var

The variety of barley ("manchuria", "svansota", "velvet", "trebi" and "peatland").

Y1

Yield in 1931.

Y2

Yield in 1932.

Source

Immer, F.R., Hayes, H.D. and LeRoy Powers (1934) Statistical determination of barley varietal adaptation. Journal of the American Society for Agronomy 26, 403--419.

Fisher, R.A. (1947) The Design of Experiments. 4th edition. Edinburgh: Oliver and Boyd.

References

Venables, W. N. and Ripley, B. D. (1999) Modern Applied Statistics with S-PLUS. Third Edition. Springer.

Examples

immer.aov <- aov(cbind(Y1,Y2) ~ Loc + Var, data = immer)
summary(immer.aov)
#>  Response Y1 :
#>             Df  Sum Sq Mean Sq F value    Pr(>F)    
#> Loc          5 17829.8  3566.0 21.8923 1.751e-07 ***
#> Var          4  2756.6   689.2  4.2309   0.01214 *  
#> Residuals   20  3257.7   162.9                      
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#> 
#>  Response Y2 :
#>             Df  Sum Sq Mean Sq F value    Pr(>F)    
#> Loc          5 10285.0 2056.99 10.3901 5.049e-05 ***
#> Var          4  2845.2  711.29  3.5928   0.02306 *  
#> Residuals   20  3959.5  197.98                      
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#> 

immer.aov <- aov((Y1+Y2)/2 ~ Var + Loc, data = immer)
summary(immer.aov)
#>             Df Sum Sq Mean Sq F value   Pr(>F)    
#> Var          4   2655   663.7   5.989  0.00245 ** 
#> Loc          5  10610  2122.1  19.148 5.21e-07 ***
#> Residuals   20   2217   110.8                     
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
model.tables(immer.aov, type = "means", se = TRUE, cterms = "Var")
#> Tables of means
#> Grand mean
#>        
#> 101.09 
#> 
#>  Var 
#> Var
#>      M      P      S      T      V 
#>  94.39 102.54  91.13 118.20  99.18 
#> 
#> Standard errors for differences of means
#>           Var
#>         6.078
#> replic.     6