Final answer:
A positive correlation is where high scores on one variable are accompanied by high scores on the second variable and low scores by low scores, signifying that variables change in the same direction. The correlation coefficient, 'r', quantifies this relationship.
Step-by-step explanation:
In statistics, a positive correlation indicates a relationship between two variables such that as the value of one variable increases, the value of the other variable also increases. Similarly, when one variable's value decreases, the second variable's value tends to decrease as well.
This type of association suggests that the variables change in the same direction. For instance, there's a typical positive correlation between height and weight; generally, taller people tend to weigh more. The correlation coefficient, denoted by 'r', quantifies this relationship and ranges from -1 to +1. A coefficient close to +1 signifies a strong positive correlation between the variables.
Conversely, a negative correlation means that as one variable increases, the other decreases. An example of this would be the relationship between the number of hours slept and levels of tiredness; typically, more sleep correlates with less tiredness. It is crucial to note that correlation does not imply causation; they merely describe how variables move in relation to one another.