Reason of Wrong Conclusions in Experiments

 

Wrong Conclusions:

How do our conclusions sometimes get wrong? We try to understand this with the following example.

We cultivated two varieties in two different fields. V2 performed better than V 1. We made a conclusion that V2 was best than V1 based on the yield obtained.

But we got surprised when cultivated V1 in both fields. We found a lot of differences between the two fields with the same variety.  What does it mean? It means that the difference was between plots instead of varieties. This difference might be due to soil heterogenicity, climate, and any other reasons. These types of differences are called experimental errors.

Therefore, correct statistical design and analysis can help us in eliminating these types of errors and making the right conclusions. The experimental errors can be minimized by replication, randomization, and blocking.