Journal of Extension System Year: 2020 (Dec), Volume: (36), Issue. (2) First page: (28) Last page: (32) Online ISSN: 2582-273X Print ISSN: 0970-2989 doi:
Development of Web Based Analysis Tool for Augmented Randomized Complete Block Design (ARCBD)
Vinay Kumar1, Sarita Rani2 , Ram Niwas3, O.P. Sheoran4,Komal Malik5
1,2,3Assistant Professor, 4Professor, Department of Mathematics and Statistics CCS HAU, Hisar-125004, 5Assistant Professor, Govt. College Nalwa, Hisar-125004
Corresponding email: email@example.com
21 Jun 2021
3 Aug 2020
4 Nov 2020
How to cite the Article
In biological and field experiments, the Augmented Randomized Complete Block Design (ARCBD) is widely used for screening and selection of a large number of germplasm lines/varieties/entries/test treatments with non replicated test treatments and replicated control treatments to estimate the experimental error. A web based online module for analysis of ARCBD was developed using scripting language Active Server Pages (ASP) based on server client architecture. The data have been taken from Federer (1956) and output compared accordingly. The outputs produced by the module are in agreement with the output generated from SAS package. An attempt was made to provide a user friendly interface for entering/pasting the data, characters names, number of observations and number of characters for analysis of augmented randomized complete block design. The module produces different output tables such as check x block table, block effects, control means and control effects, adjusted mean for test genotypes and genotypic effects. It also computes sum of squares in the analysis of variance tables after ignoring/eliminating treatment and eliminating/ignoring blocks for block and treatment effects, respectively. Critical difference table for comparing different mean differences at 5% and 1% level of significance is also given. A complete procedure is also provided in the help file to make a user friendly interface for analysis of the design.
Block design, Augmented Design, Fixed effect model, Random effect model.