What is the Difference Between Positive Correlation and Negative Correlation?

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The difference between positive correlation and negative correlation lies in the direction of change between two variables.

  • Positive Correlation: This occurs when two variables tend to move in the same direction. A positive change in one variable is accompanied by a positive change in the other variable, and vice versa. For example, there is a positive correlation between temperature and ice cream sales, as temperature increases, so do ice cream sales.
  • Negative Correlation: This occurs when two variables tend to move in opposite directions. A positive change in one variable is accompanied by a negative change in the other variable, and vice versa. For example, there is a negative correlation between the price of heating bills and the outside temperature, as the temperature decreases, the prices of heating bills increase.

Correlations can be strong or weak, depending on the closeness of the correlation coefficient to +1 or -1. The closer the coefficient is to +1 or -1, the stronger the correlation is. The closer the coefficient is to 0, the weaker it is.

Comparative Table: Positive Correlation vs Negative Correlation

The difference between positive correlation and negative correlation can be summarized in the following table:

Feature Positive Correlation Negative Correlation
Direction Two variables move in the same direction, e.g., when one variable increases, the other also increases, and vice versa. Two variables move in opposite directions, e.g., when one variable increases, the other decreases, and vice versa.
Correlation Coefficient Greater than 0, with a value closer to 1 indicating a stronger positive relationship. Less than 0, with a value closer to -1 indicating a stronger negative relationship.
Examples - Ice cream sales and hot chocolate sales
- Exercise and body fat
- Heating bill prices and outside temperature
- Tiredness during the day and sleep amount

Both positive and negative correlations can be useful in understanding relationships between variables, and the strength of the correlation can range from weak to strong, depending on the correlation coefficient value.