Analysis of factorial experiments for agronomical reseach using Infostat
DOI:
https://doi.org/10.36958/sep.v7i2.299Keywords:
factorial experiment, statistical software, analysis of variance, mean difference test, polynomial regressionAbstract
OBJECTIVE: to show researchers the statistical analysis of a two-factor experiment using software. METHOD: In the description, oat yield data are used, grown on three sowing dates and four nitrogen levels, in a randomized complete block design and combinatorial arrangement.The analysis of variance (ANOVA), verification of assumptions, interaction graph and post-ANOVA analysis were performed; using the Infostat v.2020® software. To verify the assumptions of the statistical model, the Shapiro-Wilk test was used (to verify normality) and the scatter graph between predicted values and studentized residuals (to verify homoscedasticity and independence). The DGC comparison of means was used as a post-ANOVA test. RESULTS: The summary table of the ANOVA for a two-factor experiment was generated in Infostat v.2020® along with the coefficient of variation (CV) value as an indicator of the precision of the experiment. The main factors and the interaction were significant. The p values associated with the dates, nitrogen levels, and interaction were <0.0001, 0.0034, and 0.0325. The CV was 24.67%, with a confidence interval generated by simulation of 22.27-27.07%. In the review of assumptions, these were met. According to the DGC test, the best yields were obtained on the first sowing date, and when nitrogen was applied, generating a quadratic model. CONCLUSION: The use of software allows for easy, fast, and reliable analysis. It is also possible to have more time for the interpretation of the ANOVA results.
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References
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