**positive correlation**is a relationship between variables whereby both variables move up or down in tandem. This can be contrasted with negative correlation whereby variables move in opposite directions with respect to each other. The following are hypothetical examples of a positive correlation. Play is positively correlated with creativity and imagination.Income is positively correlated to the consumption of luxury products.There is a positive correlation between ice cream sales and hot weather.Spending is positively correlated to credit card balances. Height has a positive correlation to shoe size.Rain is positively correlated to the formation of mud puddles.Snowfall is positively correlated to ski hill revenue.Technological change is positively correlated to culture change.Age is positively correlated with experience.Self-righteousness and complaining are positively correlated. Social interaction is positively correlated with happiness.Algal blooms are positively correlated to nitrogen and phosphorus fertilizer runoff.Listening to music is positively correlated with introspective thought.Price reductions and unit sales are positively correlated.

### Positive Correlation vs Null Hypothesis

A null hypothesis is a prediction that two variables aren't correlated such that an increase or decrease in one has no influence on the other. More precisely, the null hypothesis is the prediction that change to an independent variable will not correspond to change in a dependent variable.**Null Hypothesis**

Rain and mud puddles have no correlation.

### Positive Correlation vs Negative Correlation

Negative correlation is the opposite of positive correlation. For example, sleeping is negatively correlated with sleepiness such that an increase in one corresponds to a decrease in the other and vice versa. In practice, this might not be completely true as at some point oversleeping might make you sleepy.### Positive Correlation vs Causation

Correlation simply indicates that two variables move in the same direction and doesn't necessarily suggest that one causes the other to change. Confusion of correlation and causation is amongst the most common errors in research. For example, if smoking and pregnancy were correlated it would be highly unlikely that one is causing the other.**Causative Hypothesis**

Rain

**causes**mud puddles.

### Notes

Correlations can involve multiple variables. For example, wealth is positively correlated to health and education outcomes.The last example above "Price reductions and unit sales are positively correlated" can be simplified to "Price and unit sales are negatively correlated." This is the conventional way to state a hypothesis. It makes things more complex to convert a negative correlation to a positive correlation using a negation of one variable.Overview: Positive Correlation | ||

Type | ||

Definition | A relationship between variables whereby both variables move in tandem. | |

Related Concepts |