Final answer:
A positive association means that large values of one variable are associated with small values of the other. A linear association is indicated when points on a scatterplot tend to cluster around a straight line.
Step-by-step explanation:
A positive association refers to a relationship between two variables where large values of one variable are associated with small values of the other. For example, if we consider weight and height, a positive association means that as someone's weight increases, their height also tends to increase.
A positive association can also be described as a positive correlation, indicating that the variables move in the same direction. In contrast, a negative association or negative correlation means that the variables move in opposite directions. In this case, large values of one variable are associated with small values of the other.
If the points on a scatterplot, which is a graphical representation of data, tend to cluster around a straight line, it indicates that the variables plotted have a linear association. A linear association means that the relationship between the variables can be represented by a straight line.