Correlation vs. Causation

Front

What is correlation?

Back

Correlation is a statistical measure that describes the extent to which two variables change together. A positive correlation means that as one variable increases, the other also increases, while a negative correlation means that as one variable increases, the other decreases.

Front

What is causation?

Back

Causation indicates that one event is the result of the occurrence of another event. In other words, causation implies a cause-and-effect relationship between two variables.

Front

What does a correlation coefficient of r = 1 indicate?

Back

A correlation coefficient of r = 1 indicates a perfect positive correlation, meaning that as one variable increases, the other variable increases in perfect proportion.

Front

What does a correlation coefficient of r = -1 indicate?

Back

A correlation coefficient of r = -1 indicates a perfect negative correlation, meaning that as one variable increases, the other variable decreases in perfect proportion.

Front

What does a correlation coefficient of r = 0 indicate?

Back

A correlation coefficient of r = 0 indicates no correlation between the two variables, meaning that changes in one variable do not predict changes in the other.

Front

What does a correlation coefficient of r = 0.9 suggest?

Back

A correlation coefficient of r = 0.9 suggests a strong positive correlation between the two variables, indicating that as one variable increases, the other variable tends to also increase.

Front

What does a correlation coefficient of r = -0.5 suggest?

Back

A correlation coefficient of r = -0.5 suggests a moderate negative correlation, indicating that as one variable increases, the other variable tends to decrease.

Front

What is the difference between correlation and causation?

Back

Correlation does not imply causation. Just because two variables are correlated does not mean that one causes the other. There may be other factors involved.

Front

What is a scatterplot?

Back

A scatterplot is a graphical representation of two variables, where each point represents an observation. It is used to visualize the relationship between the variables.

Front

How can you determine the strength of a correlation?

Back

The strength of a correlation can be determined by the absolute value of the correlation coefficient (r). Values close to 1 or -1 indicate a strong correlation, while values close to 0 indicate a weak correlation.