How Can Data Analysis Advance Soil Science?
Analysis of variance is a crucial step in extracting information from efficiently designed experiments and surveys in soil science. Genstat offers a statistically accurate ANOVA menu for analysis of variance when comparing treatments. Multivariate analysis in Genstat can uncover patterns in multivariate soil data by means of principal components analysis, cluster analysis, canonical correlation analysis and much more.
Genstat provides an easy-to-use environment where only a few simple menu clicks are needed to undertake simple or more complex analyses, bringing reliable and accurate analytics to your soil analysis. Make predictions from large soil science data sets using data mining techniques, such as support vector machines, regression trees, random regression forests, and neural networks.
Data from diverse sources is easily imported and made ready for analysis using efficient data preparation tools, and Genstat’s data visualization options help to identify insights from your statistical analyses and truly get the most from your data.