Correlation Coefficient Practice

Front

What is the correlation coefficient (r)?

Back

The correlation coefficient (r) is a statistical measure that describes the strength and direction of a relationship between two variables, ranging from -1 to 1.

Front

What does an r value of -1 indicate?

Back

An r value of -1 indicates a perfect negative correlation, meaning that as one variable increases, the other variable decreases in a perfectly linear manner.

Front

What does an r value of 1 indicate?

Back

An r value of 1 indicates a perfect positive correlation, meaning that as one variable increases, the other variable also increases in a perfectly linear manner.

Front

What does an r value of 0 indicate?

Back

An r value of 0 indicates no correlation between the two variables, meaning there is no linear relationship.

Front

What is a strong positive correlation?

Back

A strong positive correlation is indicated by an r value close to 1, suggesting that as one variable increases, the other variable tends to also increase.

Front

What is a strong negative correlation?

Back

A strong negative correlation is indicated by an r value close to -1, suggesting that as one variable increases, the other variable tends to decrease.

Front

What is a scatter plot?

Back

A scatter plot is a graphical representation of two variables, where each point represents an observation, allowing for visual assessment of the relationship between the variables.

Front

How can you visually identify a positive correlation in a scatter plot?

Back

A positive correlation in a scatter plot is visually identified when the points tend to rise from left to right.

Front

How can you visually identify a negative correlation in a scatter plot?

Back

A negative correlation in a scatter plot is visually identified when the points tend to fall from left to right.

Front

What is the significance of the correlation coefficient in research?

Back

The correlation coefficient is significant in research as it quantifies the degree to which two variables are related, helping to inform predictions and understand relationships.