What occurs if one variable increases while the other decreases in a dataset?

• A. Positive correlation
• B. Negative correlation
• C. Causal relationship
• D. Random correlation

Answer: (B)

When one variable increases while another decreases within a dataset, this situation is described by a negative correlation. In this context, a negative correlation indicates that as the value of one variable rises, the value of the other variable tends to fall.

This relationship can often be visually represented on a scatter plot, where the trend shows points that slope downward from left to right. In practical terms, negative correlations can be seen in various real-world scenarios, such as the relationship between the amount of time spent studying (increasing) and the number of errors made on a test (decreasing) – suggesting that more study time is associated with fewer mistakes.

In contrast, positive correlation would indicate that both variables move in the same direction (both increase or both decrease), while a causal relationship involves one variable directly influencing the other, and random correlation refers to a situation where no meaningful relationship exists between the variables. Thus, identifying a negative correlation allows for an understanding of how two variables relate to one another when their movements are in opposite directions.