Correlation vs. Causation

Which example shows CAUSATION? (Which one CAUSED the other to happen.)

• High social media usage and reduced grades.

• Car ran out of gas and being stranded on the side of the road.

• Recess time and number of friends.

Which example shows CAUSATION? (Which one CAUSED the other to happen.)

• Rainfall and time spent reading.

• Eating more butter and increased divorce rates.

• It started raining and the baseball game was delayed.

Which example shows CAUSATION? (Which one CAUSED the other to happen.)

• Being happy and being a better student.

• An insect ate poison and it died.

Tags

CCSS.RI.4.3

CCSS.RI.5.3

CCSS.RI.6.3

CCSS.RI.7.3

CCSS.RI.8.3

Which example shows CORRELATION? (The events show correlation, but one thing does NOT cause the other thing to happen.)

• I put water in the freezer and now I have ice.

• The alarm clock went off and I woke up.

• Temperature and the amount of people at the beach.

Which example shows a CORRELATION? (The events show correlation, but one thing does NOT cause the other thing to happen.)

• It rained and the ground is wet.

• Ice cream sales increase as temperature increases.

Data is analyzed comparing hours studied and grades. It is determined that the correlation coefficient is 0.92. What does this mean?

• There is a strong positive correlation between studying and grades.

• There is a strong negative correlation between studying and grades.

• There is a weak positive correlation between studying and grades.

• There is a weak negative correlation between studying and grades.

Data is collected comparing sales of cars and the age of the salesperson. After analyzing the data, it is determined that the correlation coefficient is 0.19. What does this mean?

• There is no correlation between sales and age.

• There is a strong positive correlation between sales and age.

• There is a strong negative correlation between sales and age.

• There is a weak negative correlation between sales and age.

Data is collected comparing minutes of exercise each day and blood pressure. It is determined that the correlation coefficient is -0.87. What does this mean?

• There is a strong negative correlation between exercise and blood pressure.

• There is a weak negative correlation between exercise and blood pressure.

• There is a strong positive correlation between exercise and blood pressure.

• There is no correlation between exercise and blood pressure.

A correlation shows that two things are

• related
• causing each other
• unrelated

This implies that one variable has a direct affect on the other variable.

• Correlation
• Causation