Question

Soy beans type 1 yielded 125 bushels per acre last year at a research farm. This year, soy bean type 2, planted in the same location, yielded only 100 bushels per acre and there was a drought. The researchers do not know whether the difference is a result of the superiority of type 1 soy beans or the drought. What is this an example of?

1) Bias
2) Matched-pairs design
3) The placebo effect
4) Confounding variable
5) Replication

Answer 1

The difference in yield between soybean type 1 and type 2, with the latter experiencing a drought, is an example of a confounding variable that complicates the determination of whether the yield difference is due to the soybean type or the effects of the drought.

Step-by-step explanation:

The scenario you have described, where soybean type 1 yielded 125 bushels per acre last year and soybean type 2 yielded only 100 bushels per acre this year in the presence of a drought, is an example of a confounding variable.

This means there is an outside influence that affects the dependent variable, which in this case is the yield of soybeans.

The drought represents a confounding variable because it could be the primary cause for the lower yield of soybean type 2, rather than the inherent yield capacity of soybean type 2 itself.

It is challenging for the researchers to determine whether the difference in yield between the two types of soybeans is due to the superiority of type 1 or the impact of the drought.

Natural conditions such as drought can significantly affect the supply of agricultural products.