A nuisance, or 'confounding' variable makes understanding the relationship between the independent and dependent variables difficult because:
A) it provides a competing explanation other than the independent variable for changes in the dependent variable.
B) it does not take into account things done by workers that spoil research results.
C) the distribution is altered such that it is impossible to reject the null hypothesis.
D) nuisance variables lack controls.

Question

Quizplus · Accepted Answer

A nuisance (or confounding) variable is not of theoretical interest to the researcher, but is correlated with the independent variable in a study. This means a nuisance or confounding variable provides a competing explanation, other than the independent variable, for changes in the dependent variable. For example: assume the number of shark attacks is the dependent variable. People eat lots of ice cream in summer: does this cause shark attacks? Not necessarily: in hot weather people spend more time in the water and, coincidently, eat more ice cream. Thus, we may be concerned with the time of year, or time spent in the water rather than ice cream consumption (our nuisance variable). Incidentally, a variable such as this may exhibit a relationship which we would term a 'spurious correlation'.

A Nuisance, or 'Confounding' Variable Makes Understanding the Relationship Between