This describes a discrete variable, which is defined by having a countable number of possible values, rather than a confounding variable.

A value that remains constant is simply a constant or a controlled variable, whereas a confounding variable varies and affects the outcome.

This describes the explanatory (or independent) variable, which is the specific factor the researcher is studying to see if it causes a change.

A confounding variable is an outside influence that affects the response variable and is related to the explanatory variable, making it difficult to determine the true cause of the observed effect.

This is incorrect because a 'negative' relationship implies that as one variable increases, the other decreases. Additionally, observational data establishes association, not necessarily causation.

This is incorrect because correlation does not imply causation. While the variables move together, it is likely a third variable (like hot weather) causes both to increase, rather than ice blocks causing fan sales.

This is incorrect because a negative association describes an inverse relationship where one variable decreases as the other increases, contradicting the observation that both increase.

This is correct because 'positive' indicates that both variables move in the same direction (both increase), and 'association' correctly describes the statistical relationship without assuming one causes the other.