Correlation Definition
Correlation refers to the statistical relationship between two or more variables. It measures the degree to which changes in one variable are associated with changes in another variable. Correlation does not imply causation, meaning that just because two variables are correlated does not necessarily mean that changes in one variable cause changes in the other. Correlation can be positive, negative, or zero.
- Positive correlation: As one variable increases, the other variable also tends to increase.
- Negative correlation: As one variable increases, the other variable tends to decrease.
- Zero correlation: There is no consistent relationship between the variables.
Correlation is measured using correlation coefficients such as Pearson’s correlation coefficient or Spearman’s rank correlation coefficient. These coefficients range from -1 to 1, where -1 indicates a perfect negative correlation, 1 indicates a perfect positive correlation, and 0 indicates no correlation.
Real-Life Applications of Correlation and Regression
Correlation and regression analysis represent useful discrimination and classification tools in statistics which find applications in different fields and disciplines. Correlation serves to detect interrelationships among the different variables and unravels the unseen patterns which might be otherwise hidden. From economics, to psychology, and public health, knowing correlation ensures that decisions are based on evidence and predictions are informed as well.
In this article , we’ll look into Real-life applications of correlation and regression.