Parameters of the statistical model in the linear relationships of growthpromoting bacteria in soybean

ABSTRACT In multivariate statistical analyses, the parameters of the statistical model referring to the experimental design are disregarded, so in general researchers work with average observations, without stratification of effects. The objective was to evaluate and characterize the effects of removing the effect of parameters from the statistical model on the linear relationships between variables in growth-promoting and phosphorus (P)-solubilizing bacteria in soybean crop. The design used was randomized blocks in a 9 x 4 two-factor arrangement, with four replicates. The first factor, Bradyrhizobium spp. co-inoculated with: 1) Azospirillum spp.; 2) Pseudomonas fluorescens; 3) Bacillus subtilis; 4) Bacillus subtilis + Bacillus megaterium; 5) Azospirillum spp. + Pseudomonas fluorescens; 6) Azospirillum spp. + Bacillus subtilis; 7) Azospirillum spp. + Bacillus subtilis + Bacillus megaterium; 8) Azospirillum spp. + Pseudomonas fluorescens + Bacillus subtilis + Bacillus megaterium and 9) Control (without bacteria); and four doses of P2O5: 0, 50, 100 and 150 kg ha-1. Statistical assumptions were tested and parameters were removed from the statistical model, stratifying effects, and the change was compared to the traditional analysis (general model), in the principal component and Pearson's correlation analyses. Treatment with Bradyrhizobium spp. + Azospirillum spp. + Bacillus subtilis showed the highest percentage of accumulated variance, 56.99%. Removal of parameters changed the magnitude of Pearson's correlation coefficients, from 10% to 70% and the direction by up to 54.55%.