The reports contained in this booklet are the results of the research plot work conducted at Farm Focus.  Most of the research conducted by Van Wert County Extension is systematically designed to allow for statistical analysis of the results.  To achieve this we utilize three key statistical concepts: randomization, blocking, and replication.  We also had a trial where we did a comparison between only two treatments in a split-planter design.  This simple setup allows for paired treatment blocking and replication, but no randomization.  This booklet also contains a useful OSU factsheet that explains statistics and the above concepts in more detail. Below are some definitions of common statistical references used in this book:

F-test- The F statistic is used to help identify if the differences between treatment means are due to background noise or the actual treatment.  If there are no differences between treatments, the F statistic will be less than or near 1.

LSD (0.05) - Least Significant Difference (LSD) tests for significance between individual treatments.  Two treatments are considered statistically different if they differ by more than the LSD.  For example, if a given treatment yields different from another treatment by as much or more than the LSD (0.05) value, then we are 95% confident that the yield difference is due to the treatment and not some other factor.

CV (Coefficient of Variation) - The CV is a measure of relative variation.  A lower CV indicates less variation within the trial for the measured observation.

Paired t-test – This test looks at the differences between two paired treatments and reports the probability that the mean differences are significant when compared to the expected t-value (expected t-value varies based on the number of replications of the paired treatments).

Statistically significant difference - A difference that is beyond what might be expected by chance alone. 

We believe this booklet provides a valuable, unbiased source of information for farmers to use as a decision making tool in their operation.  We also believe it is best to utilize multiple sources of information when making an informed decision before adopting new agronomic products and practices.