Association vs. Causation

What is the difference between association and causation?

• Association is a type of relationship, while causation is a type of correlation.

• Association is a statistical relationship, while causation implies a direct cause and effect relationship.

• Association is based on observational data, while causation is based on experimental data.

• Association is a weak relationship, while causation is a strong relationship.

Define correlation.

• Correlation is a mathematical operation used to calculate the average of two variables.

• Correlation is a measure of the strength and direction of the linear relationship between two variables.

• Correlation is a statistical measure that describes the relationship between two variables.

• Correlation is a method used to determine causation between two variables.

Define causation.

• Causation is the relationship between effect and cause.

• Causation is the relationship between correlation and effect.

• Causation is the relationship between cause and effect.

• Causation is the relationship between consequence and cause.

Can correlation imply causation? Why or why not?

• Yes, because correlation always implies causation

• Yes, because correlation and causation are the same thing

• No

• Yes, because correlation is a strong indicator of causation

Give an example of a correlation without causation.

• The number of books read and the number of hours spent studying

• Ice cream sales and shark attacks

• The number of firefighters and the number of fires

• Rainfall and the number of umbrellas sold

Give an example of causation without correlation.

• Eating ice cream and getting sunburned.

• Drinking coffee and feeling tired.

• Taking a painkiller to relieve a headache.

• Wearing a raincoat and it raining.

What are some factors to consider when determining causation?

• Coincidence, random chance, astrology

• Correlation, temporal relationship, dose-response relationship, consistency, plausibility, coherence, and experimental evidence.

• Personal beliefs, anecdotal evidence, popularity

• Association, sample size, statistical significance

Explain the phrase 'correlation does not imply causation'.

• Correlation and causation are the same thing.

• Correlation implies causation.

• Correlation does not imply causation.

• Causation implies correlation.

Why is it important to understand the difference between association and causation?

• To make assumptions without any evidence or reasoning.

• To waste time and effort on irrelevant information.

• To avoid making false assumptions or drawing incorrect conclusions.

• To confuse people and make them draw incorrect conclusions.

How can experiments help establish causation?

• Experiments manipulate variables and observe the effects to establish causation.

• Experiments can only establish correlation, not causation.

• Observation alone is sufficient to establish causation.

• Experiments have no effect on establishing causation.