Scatterplot Correlation and Causation

Will the variables below show correlation and causation, correlation only, or no relationship?

The number of snow plows owned by a city and mitten sales in the city.

• Correlation with causation

• Correlation without causation

• No relationship

Will the variables below show correlation and causation, correlation only, or no relationship?

The number of text messages sent per day by a person and number of shirts owned by the person.

• Correlation with causation

• Correlation without causation

• No relationship

Will the variables below show correlation and causation, correlation only, or no relationship?

The price of a pizza and number of calories in the pizza.

• Correlation with causation

• Correlation without causation

• No relationship

Will the variables below show correlation and causation, correlation only, or no relationship?

The amount of gas used on a trip and number of miles driven on the trip.

• Correlation with causation

• Correlation without causation

• No relationship

Will the variables below show correlation and causation, correlation only, or no relationship?

Priya creates a scatter plot showing the relationship between the number of steps she takes and her heart rate. The correlation coefficient of the line of best fit is 0.88.

• Correlation with causation

• Correlation without causation

• No relationship

Will the variables below show correlation and causation, correlation only, or no relationship?

Kiran creates a scatter plot showing the relationship between the number of students attending drama club and the number of students attending poetry club each week. The clubs meet at different times, so it is possible to be in both clubs at once. The correlation coefficient for the line of best fit is -0.16.

• Correlation with causation

• Correlation without causation

• No relationship

Will the variables below show correlation and causation, correlation only, or no relationship?

A news website shows a scatter plot with a negative relationship between the amount of sugar eaten and happiness levels. The headline reads, “Eating sugar causes happiness to decrease!”

• Correlation with causation

• Correlation without causation

• No relationship