References

Shimizu, G. D., Marubayashi, R. Y. P. and Gonçalves, L. S. A. (2024). AgroR: Experimental Statistics and Graphics for Agricultural Sciences. R package version 1.3.6. Disponível em: https://cran.r-project.org/web/packages/AgroR/index.html

Data insert
Help

Browse...

Tab

Separation CSV

Decimal CSV

Number of factors

1 2 3

Treatments

Response Variable

Data Input

The AgroR Shiny App allows the entry of data from files in .csv extension (Separated by comma, period or semi-colon), .xls or .xlsx. The data entry parameters change according to the number of factors.

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

Analysis

The 'Descriptive Analysis' tab, in 'Summary', calculates the mean, median, sample variance, sample standard deviation and general and separate coefficient of variation according to the factor levels
In this tab, under 'Graphics', general box plots are returned, separated by factors.

General summary

Factor 1 summary

Factor 1 name

Factor 2 name

Factor 3 name

Width figure

Height figure

Completely Randomized design

Download csv Download xlsx Data set 'romã'

Download csv Download xlsx Data set 'bean'

Download csv Download xlsx Data set 'pepper'

Design in randomized blocks

Download csv Download xlsx Data set 'orange'

Download csv Download xlsx Data set 'soybean'

Latin square design.

Download csv Download xlsx Data set 'pork'

Completely randomized design in a double factorial scheme

Download csv Download xlsx Data set 'dosecultivar'

Design in randomized blocks in a double factorial scheme

Download csv Download xlsx Data set 'cloro'

Download csv Download xlsx Data set 'covercrops'

Randomized block design in a split-plot scheme

Download csv Download xlsx Data set 'tomato'

Data insert
Help

Browse...

Tab

Separation CSV

Decimal CSV

Treatments

Response Variable

Treatments

Lines

Column

Response Variable

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 dunnett test for experiments conducted in a completely randomized design and randomized blocks. The output of the analysis is basically divided into: Contrasts between treatments and a graph with confidence interval.

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 enter the data and define which column refers to the treatment and the response variable. It is also necessary to define which level of the factor is represented by the witness (the name must be identical to the one written in the worksheet)

Once entered the information, the user can click on the 'RUN' button:

Contrasts

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.

Plots

Finally, on the 'Graph' tab, a graph is returned with the estimates of contrasts and the confidence interval.

Download

File name

Format

Resolution (dpi)

Width figure

Height figure

Data insertion

Function under development (Wait for completion)

Browse...

tab

CSV separation

Decimal CSV

Treatments

Response variable

Download

Name report

Format

Resolution (dpi)

Width figure

Height figure

Graphic type

Text size

Label size

Label space

Angle axis

Number of decimal places

Legend position

Label angle

Add error bar

Add mean

Data insert
Help

Browse...

Tab

Separation CSV

Decimal CSV

Treatments

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...

Graphics parameters

Width Figure

Height Figure

Graph type

Text size

Label size

How many above the bar?

Axis angle

Number of decimal places

Legend position

Label angle

Add error bar

Add mean

Enter QMres values (Separate numbers by a comma and decimal by a point)

Matrix All vs All

Orderly ratio.

Ratio reference

Clustering

Number of cluster

Clustering method

Data insert
Help

Browse...

Tab

Separation CSV

Decimal CSV

Treatments

Block

Experiment

Response variable

Ratio Qmres reference

Qualitative

Mean test

Data insert
Help

Browse...

Tab

Separation CSV

Decimal CSV

Response Variable

Mean

Welcome to AgroR Shiny!!!

References

Completely Randomized design

Design in randomized blocks

Latin square design.

Completely randomized design in a double factorial scheme

Design in randomized blocks in a double factorial scheme

Randomized block design in a split-plot scheme

This function is equivalent to AgroR's summarise_anova

Transformação

Function under development (Wait for completion)

Matrix All vs All

Orderly ratio.

Clustering

Text: