invert uppercase and lowercase letters in graph for factorial scheme the subdivided plot with significant interaction

ibarplot.double(analysis)

## Arguments

analysis

FAT2DIC, FAT2DBC, PSUBDIC or PSUBDBC object

## Value

Return column chart for two factors

## Examples

data(covercrops)
attach(covercrops)
#> The following objects are masked from covercrops (pos = 4):
#>
#>     A, B, Bloco, Resp
a=FAT2DBC(A, B, Bloco, Resp, ylab=expression("Yield"~(Kg~"100 m"^2)),
legend = "Cover crops",alpha.f = 0.3,family = "serif")
#>
#> -----------------------------------------------------------------
#> Normality of errors
#> -----------------------------------------------------------------
#>                          Method Statistic   p.value
#>  Shapiro-Wilk normality test(W) 0.9758908 0.6061712
#>
#> As the calculated p-value is greater than the 5% significance level, hypothesis H0 is not rejected. Therefore, errors can be considered normal
#>
#> -----------------------------------------------------------------
#> Homogeneity of Variances
#> -----------------------------------------------------------------
#>                               Method Statistic   p.value
#>  Bartlett test(Bartlett's K-squared)  10.19232 0.2517862
#>
#> As the calculated p-value is greater than the 5% significance level, hypothesis H0 is not rejected. Therefore, the variances can be considered homogeneous
#>
#> -----------------------------------------------------------------
#> Independence from errors
#> -----------------------------------------------------------------
#>                  Method Statistic   p.value
#>  Durbin-Watson test(DW)  2.335214 0.3781148
#>
#> As the calculated p-value is greater than the 5% significance level, hypothesis H0 is not rejected. Therefore, errors can be considered independent
#>
#> -----------------------------------------------------------------
#> Additional Information
#> -----------------------------------------------------------------
#>
#> CV (%) =  2.65
#> Mean =  37.4583
#> Median =  37.45
#> Possible outliers =  No discrepant point
#>
#> -----------------------------------------------------------------
#> Analysis of Variance
#> -----------------------------------------------------------------
#>               Df     Sum Sq   Mean.Sq   F value        Pr(F)
#> Fator1         2 146.585000 73.292500 74.645449 4.979960e-11
#> Fator2         2  23.021667 11.510833 11.723318 2.805884e-04
#> bloco          3   2.167500  0.722500  0.735837 5.409183e-01
#> Fator1:Fator2  4   6.008333  1.502083  1.529811 2.252749e-01
#> Residuals     24  23.565000  0.981875
#>
#> -----------------------------------------------------------------
#>
#> Significant interaction: analyzing the interaction
#>
#> -----------------------------------------------------------------
#>
#> -----------------------------------------------------------------
#> Analyzing  F1  inside of each level of  F2
#> -----------------------------------------------------------------
#>                     Df  Sum Sq Mean Sq F value    Pr(>F)
#> bloco                3   2.168   0.723  0.7358 0.5409183
#> Fator2               2  23.022  11.511 11.7233 0.0002806 ***
#> Fator2:Fator1        6 152.593  25.432 25.9017 2.296e-09 ***
#>   Fator2:Fator1: B1  2  51.165  25.583 26.0547 9.667e-07 ***
#>   Fator2:Fator1: B2  2  34.427  17.213 17.5311 2.027e-05 ***
#>   Fator2:Fator1: B3  2  67.002  33.501 34.1192 9.629e-08 ***
#> Residuals           24  23.565   0.982
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> -----------------------------------------------------------------
#> Analyzing  F2  inside of the level of  F1
#> -----------------------------------------------------------------
#>
#>                     Df  Sum Sq Mean Sq F value   Pr(>F)
#> bloco                3   2.168   0.723  0.7358 0.540918
#> Fator1               2 146.585  73.293 74.6454 4.98e-11 ***
#> Fator1:Fator2        6  29.030   4.838  4.9276 0.002054 **
#>   Fator1:Fator2: A1  2   1.995   0.998  1.0159 0.377120
#>   Fator1:Fator2: A2  2  15.495   7.748  7.8905 0.002325 **
#>   Fator1:Fator2: A3  2  11.540   5.770  5.8765 0.008371 **
#> Residuals           24  23.565   0.982
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> -----------------------------------------------------------------
#> Final table
#> -----------------------------------------------------------------
#>          B1      B2      B3
#> A1  34.5 bA 34.8 bA 35.4 cA
#> A2 37.8 aAB 36.2 bB 39.0 bA
#> A3  39.4 aB 38.9 aB 41.1 aA
#>
#>
#> Averages followed by the same lowercase letter in the column
#> and uppercase in the row do not differ by the tukey (p< 0.05 )

ibarplot.double(a)