Unit seven scatterplot and data analysis lesson five correlation
Correlation is a statistical measure that describes the relationship between two variables. It indicates the extent to which two variables change in relation to each other.
There are different types of correlation:
1. Positive correlation: When the values of one variable increase, the values of the other variable also increase. In other words, the variables move in the same direction.
2. Negative correlation: When the values of one variable increase, the values of the other variable decrease. In other words, the variables move in opposite directions.
3. No correlation: When there is no relationship between the two variables. The values of one variable do not have any impact on the values of the other variable.
Correlation is usually measured on a scale from -1 to 1. A correlation of 1 indicates a perfect positive correlation, -1 indicates a perfect negative correlation, and 0 indicates no correlation.
Correlation can help us understand the relationship between different variables and can be useful in making predictions or identifying patterns in data. However, it is important to remember that correlation does not imply causation – just because two variables are correlated does not mean that one causes the other.