Note: The tabulation of data must be done in columns, each one being represented by a factor or response variable according to the number of categories

In this tab, under 'Graphics', general box plots are returned, separated by factors.

In treatments, you can define the number of factor levels or write the name of the treatments separated by ';'. For example 5 or 1; 2; 3; 4; 5.

It is possible to change rows by columns through the 'Position of repetitions' window. This changes the matrix from 5 x 4 to 4 x 5 for example.

To add streets on the x and y axis via the 'Add streets x-axis' and 'Add streets y-axis' windows, type the number of columns with x or y axis you want to join. For example, suppose you have 5 rows and 4 columns and you want add a street between the second and third column, it must be add in 'Add streets in x axis' the following order 1;1;2;2

In the box 'Do you want to represent only identification?', if the option 'Yes' is checked, only the identification and a dataset.csv file will be returned.

In the box 'Do you want to fix a sketch?', it allows to always generate the same sketch layout. Provide the model in 'What is the model?'.

Download csv
Download xlsx
Data set 'romã'

Download csv Download xlsx Data set 'bean'

Download csv Download xlsx Data set 'pepper'

Download csv Download xlsx Data set 'bean'

Download csv Download xlsx Data set 'pepper'

Download csv
Download xlsx
Data set 'pork'

Download csv
Download xlsx
Data set 'tomato'

Note: The tabulation of the data must be done in columns, each one being represented by a factor or response variable according to the experimental design

The assumption of normality of errors and homogeneity of variances is returned in the 'Assumptions' window. In this case, you can change the desired tests. The exception is for the error independence test, which only the Durbin-Watson test is implemented.

In the graphic window 'Graph of residuals', the graphic of standardized residuals is returned. In this topic, it is possible to identify the presence of outliers. In the graphic, limits -3 and 3 are used as a way of identifying these outliers.

In the graphical window 'Complementary tests', the average or regression tests are returned. In this topic, you must inform whether the factor or factors have qualitative (default) or quantitative levels. It is also in this topic that you define which average test you want to use and/or what degree of polynomial (in case of quantitative factor).

In the case of more than one factor studied, such as a factorial scheme or subdivided plot, and when there is significant interaction, use comma separation to define the degree of the polynomial.

To choose the degree of the polynomial, use 0 (Not significant), 1 (linear), 2 (quadratic) and 3 (cubic).

*sw: Shapiro-Wilk, li: Lilliefors, ad: Anderson-Darling, cvm: Cramer-von Mises, pearson: Pearson and sf: Shapiro-Francia

**bt: Bartlett; levene: Levene

Independence from errors (Durbin-Watson)

Interpretation: p value higher than the adopted significance level (generally 0.05), the null hypothesis is not rejected (Errors follow normal distribution, treatments have the same variance and errors are independent).

Note. The tabulation of data must be done in columns, each one being represented by a factor or response variable

Once the commands have been executed, the contrasts with the reference treatment are returned in the 'Dunnett's Test' window. This table returns the estimate of the contrast, the confidence interval (Lower and Upper), the value of the test statistic ( t), the value of p and whether there was a significant difference.

The AgroR Shiny App allows the input of data in .csv extension (Separated by comma, period or semi-colon), .xls or .xlsx

Note. The tabulation of data must be done in columns, each one being represented by a factor or response variable

# Analysis

## General Painel

The application performs the Kruskal-Wallis or Friedman non-parametric test for experiments conducted in a completely randomized design and randomized blocks, respectively.
## Definition of parameters for analysis

The application requires that certain parameters be defined before the analysis. In the window below, you must define the experimental design used:
Next, you must insert the data and define which column refers to the treatment and the response variable.
Once entered the information, the user can click on the 'RUN' button
## Test statistics

Once the commands are executed, the 'Non-parametric test' window returns the test statistics and p value.

## Post-hoc test

On the 'Complementary test' tab, the non-parametric mean test is returned (the value corrections can be changed using the button located below the experimental design.
## Graphics

Finally, in the 'Graph' tab, a column, box or point graph is returned. Changing various parameters of the graph, such as color, font size, font, dimension, axis name, etc...

Note. The tabulation of data must be done in columns, each one being represented by a factor or response variable

Once the commands are executed, the 'Non-parametric test' window returns the test statistics and p value.

On the 'Complementary test' tab, the non-parametric mean test is returned (the value corrections can be changed using the button located below the experimental design.

Note. The tabulation of data must be done in columns, each one being represented by a factor or response variable

Note. The tabulation of data must be done in columns, each one being represented by a factor or response variable