Multiple Comparison of Means in Empirical Agricultural Researches

Shumetov, Vadim; Kolomeichenko, A. V.; Buyarov, V.S.; Metasova, S.Yu.

doi:10.15217/issn1990-3618.2017.4.113

Cited by 2 publications

(2 citation statements)

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“…Various authors pointed out disadvantages in the use of new data analysis technologies in the practice of agricultural research [5,6]. For example, V.M.…”

Section: Literary Reviewmentioning

confidence: 99%

Technologies of intellectual analysis of the data in agricultural research

Buyarov¹,

Shumetov²,

Buyarov³

et al. 2019

Proceedings of the International Scientific and Practical Conference “Digital Agriculture - Development Strategy” (ISPC 2019)

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An important factor in increasing the efficiency of decisions made on the results of agricultural research is the use of advanced digital economy technologies. However, in practice, the analysis of empirical results is often limited to a pairwise comparison of means on impact options, without taking into account the realities of the plan of laboratory or field experiments. The possibility of obtaining new knowledge using information technologies for the analysis of empirical data that support algorithms for multiple comparison of means and multivariate analysis of variance is discussed. To implement these algorithms, you do not need to access expensive software products of the Data Mining class (DM); it is enough to have relatively inexpensive statistical data analysis packages such as early versions of SPSS (Statistical Package for the Social Sciences) starting from version 8.0. An example is given to illustrate the effectiveness of using information systems of the Knowledge Discovery class, focused on the data knowledge search.

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“…Various authors pointed out disadvantages in the use of new data analysis technologies in the practice of agricultural research [5,6]. For example, V.M.…”

Section: Literary Reviewmentioning

confidence: 99%

Technologies of intellectual analysis of the data in agricultural research

Buyarov¹,

Shumetov²,

Buyarov³

et al. 2019

Proceedings of the International Scientific and Practical Conference “Digital Agriculture - Development Strategy” (ISPC 2019)

View full text Add to dashboard Cite

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“…In the work [5], on the example of the study on the effect of the probiotic "Olin" on the live weight of broilers, it is shown that a multiple comparison of the averages upon criteriumSheffe test using the procedure of a generalized linear model gives the researcher comprehensive information about the reliability of statistical conclusions. It is noted that if the number of variants in the experiment is not large (up to four), then for their comparison you can rely on the LSR criterion, but the maximum comparison accuracy is achieved for only one pair of averages, and rank criteria should be used to increase the accuracy of the comparison [6].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the influence of sowing time on yield and quality of the wheat grain using Multivariate dispersion analysis

et al. 2021

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The statistical analysis of the results of studies on the effect of sowing time on the yield and quality of winter wheat grains, from the perspective of multivariate variance analysis and multiple comparison of averages, is carried out in the article. It was found that the application of the procedure of a multivariate generalized linear model allows comparing the variants of experiments for all indicators in the aggregate. An important advantage of multiple comparisons over paired Student comparisons is also the ability to isolate homogeneous subgroups of experiments. In this study, post hoc comparisons according to the Tukey criterion were applied, the results of which are presented in tables of homogeneous experiment subgroups and multiple comparisons of indicators’ differences. The distribution of experiment variants by zones of desirability of Harrington functions of yield and generalized indicator of grain quality, depending on shift of sowing time is also presented. It is justified that the maxima of yield and quality of winter wheat grains provide a sowing period of 10 days later than previously recommended for the region. The use of multivariate dispersion analysis and multiple comparison of average increases the reliability of statistical conclusions, allows you to distinguish homogeneous versions of experiments in agricultural production.

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Multiple Comparison of Means in Empirical Agricultural Researches

Cited by 2 publications

References 0 publications

Technologies of intellectual analysis of the data in agricultural research

Technologies of intellectual analysis of the data in agricultural research

Evaluation of the influence of sowing time on yield and quality of the wheat grain using Multivariate dispersion analysis

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