Correlation vs Causation

Front

What is the definition of Causation?

Back

Causation refers to a relationship where one event (the cause) directly affects another event (the effect).

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What is the definition of Correlation?

Back

Correlation is a statistical relationship between two variables, where changes in one variable are associated with changes in another, but one does not cause the other.

Front

Example of Causation: If I water a plant, it grows. What does this illustrate?

Back

This illustrates that watering the plant (cause) directly leads to its growth (effect).

Front

Example of Correlation: Ice cream sales increase as temperature rises. What does this illustrate?

Back

This illustrates a correlation where both ice cream sales and temperature increase together, but one does not cause the other.

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What is a key difference between Correlation and Causation?

Back

The key difference is that causation implies a direct cause-and-effect relationship, while correlation indicates a relationship without direct causation.

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Can correlation imply causation?

Back

No, correlation does not imply causation. Just because two variables are correlated does not mean one causes the other.

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What is an example of a spurious correlation?

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A spurious correlation is when two variables appear to be related but are actually influenced by a third variable, like ice cream sales and drowning incidents both increasing in summer.

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What is the importance of understanding correlation vs causation in research?

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Understanding the difference helps avoid incorrect conclusions about relationships between variables and ensures accurate interpretations of data.

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What does it mean if two variables have a negative correlation?

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A negative correlation means that as one variable increases, the other variable tends to decrease.

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What does it mean if two variables have a positive correlation?

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A positive correlation means that as one variable increases, the other variable also tends to increase.