A negative correlation is a relationship between variables whereby they go in an opposite direction with respect to each other. This doesn't necessarily imply a causal relationship whereby one directly influences the other. The following are hypothetical examples of negative correlation.Coffee is negatively correlated to tiredness in regular coffee drinkers.Rain is negatively correlated to bicycle traffic.After age 20, there is a negative correlation between age and health.Smoking is negatively correlated to good health.
Alcohol consumption is negatively correlated to cognitive performance such as judgement.Exercise is negatively correlated with non-muscle body mass.Listening to music is negatively correlated to boredom.There is a negative correlation between income and the consumption of inferior goods.There is a negative correlation between speed and car accident survival.Employment income is negative correlated to free time.Difficult to open packaging is negatively correlated with customer satisfaction.Concentration level has a negative correlation with task completion time.For students, time on social media is negatively correlated to time studying.Vehicle weight is negatively correlated with energy efficiency.Brushing teeth is negatively correlated with cavities.Poverty is negatively correlated to education achievement. Running distance has a negative correlation with running pace.There is a negative correlation between altitude and temperature.Notes
Negative correlation is bidirectional whereby if one variable increases, the other decreases and vice versa. As such the following two statements have different meanings as the latter implies a correlation that only runs in one direction.Exercise is negatively correlated with non-muscle body mass.
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Exercise reduces non-muscle body mass.
Summary
A negative correlation is when two variables run in opposite directions with respect to each other. This can be based on causation whereby one variable influences the other. However, negative correlations can also be random or can be based on a third variable that influences both correlated variables in opposite directions.Next: Correlation
