Correlation vs. Causation

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What is correlation?

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Correlation is a statistical measure that describes the extent to which two variables change together. A positive correlation means that as one variable increases, the other also increases, while a negative correlation means that as one variable increases, the other decreases.

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What is causation?

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Causation indicates that one event is the result of the occurrence of another event. In other words, causation implies a cause-and-effect relationship between two variables.

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What does a correlation coefficient of 0 indicate?

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A correlation coefficient of 0 indicates no correlation between the two variables, meaning that changes in one variable do not predict changes in the other.

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What does a correlation coefficient of 1 indicate?

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A correlation coefficient of 1 indicates a perfect positive correlation, meaning that as one variable increases, the other variable increases in a perfectly linear manner.

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What does a correlation coefficient of -1 indicate?

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

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CCSS.HSS.ID.B.5

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What does a correlation coefficient of 0.19 suggest?

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A correlation coefficient of 0.19 suggests a weak positive correlation between the two variables.

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What does a correlation coefficient of 0.92 suggest?

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A correlation coefficient of 0.92 suggests a strong positive correlation between the two variables.

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What is an example of correlation without causation?

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An example of correlation without causation is the increase in ice cream sales as the temperature rises. While both variables increase together, one does not cause the other.

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What is an example of causation?

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An example of causation is putting water in the freezer to make ice. The action of freezing causes the water to turn into ice.

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How can you visually assess correlation?

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You can visually assess correlation by using a scatterplot, where each point represents a pair of values. The pattern of the points can indicate the type of correlation.

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