Answer:
Step-by-step explanation:
Hello!
To see if there is an association between the variables:
"Level of satisfaction of an individual"
"Risk of diabetes of an individual"
The researchers studied 1621 people over 5 years.
Observations recorded:
Interviews of daily lives and hassles and hypothetical situations that were studied to assess their emotions.
Determination, if in the course of these 5 years the individuals experienced any type of diabetes.
Conclusion "Satisfied individuals are less likely to have diabetes"
a) This is a prospective cohort study.
In this type of study, a group of individuals that share the same characteristics is observed over some time, recording the events of interest.
b) Considering that the experiment concluded that "satisfaction" reduces the "risk of diabetes", we can determine that the response variable is "Risk of diabetes of an individual" and the explanatory variable is "Level of satisfaction of an individual".
Remember, the explanatory variable is the one considered to have a direct effect over the response variable.
c) "the research team also hasn't ruled out that a common factor like genetics could be causing both the emotions and the lung cancer."
There is a new variable that may affect the experiment. Be "genetic factor" the new variable and it affects directly "emotions and lung cancer", we can say that if some of those individuals are genetically predisposed to have lung cancer, this affects their emotions (satisfaction) and therefore, modifying their risk of having diabetes.
If this is so, then the genetic factor could be a lurking variable affecting directly the result of the observational experiment. Then the correct answer is:
A. The researchers may be concerned with confounding that occurs when the effects of two or more explanatory variables are not separated or when some explanatory variables were not considered in a study, but that affects the value of the response variable.
I hope it helps!