Question

Banana tree type 1 yielded 135 bushels per acre last year at a research farm, and the farm experienced a drought. This year, banana

tree type 2, planted in the same location, yielded 167 bushels per acre. The researchers do not know whether the difference is a result

of the superiority of type 2 banana trees or the drought. What is this an example of?

A. Confounding variable

B. Bias

C. Matched pairs design

D. The placebo effect

E. Replication

Answer 1

confounding variable

Explanation:

i took the test, and this is the answer because the outside variable of the drought is not allowed to be eliminated while analyzing the results of the study. The drought must be accounted for,

Answer 2

A) Confounding variables.

Explanation:

Confounding variable or Lurking variable is a variable that influences both the

dependent variable and independent variable , causing a spurious

association . Confounding is a causal concept, and as such, cannot

be described in terms of correlations or associations.

In an experiment, the independent variable

typically has an effect on your dependent

variable. For example, if you are researching

whether lack of exercise leads to weight gain,

lack of exercise is your independent variable

and weight gain is your dependent variable.

Confounding variables are any other variable

that also has an effect on your dependent

variable. They are like extra independent

variables that are having a hidden effect on

your dependent variables.

Here, 2 species of banana trees were planted and studied to see which one yields more fruit than the other(dependent and independent variables),but the confounding variable(drought) which wasn't into consideration came in to possibly alter the final results.