Correlation & 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. It implies a direct cause-and-effect relationship between two variables.

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What is a correlation coefficient?

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A correlation coefficient is a numerical measure of the strength and direction of a relationship between two variables, ranging from -1 to +1.

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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 decreases 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 positive correlation, meaning that as one variable increases, the other also increases in a perfectly linear manner.

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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 is a weak negative correlation?

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A weak negative correlation is indicated by a correlation coefficient closer to 0 (e.g., -0.34), suggesting a slight inverse relationship between the two variables.

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What is a strong negative correlation?

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A strong negative correlation is indicated by a correlation coefficient closer to -1 (e.g., -0.87), suggesting a strong inverse relationship between the two variables.

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What is a scatterplot?

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A scatterplot is a graphical representation of two variables, where each point represents an observation. It helps visualize the relationship between the variables.

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How can you estimate the correlation coefficient from a scatterplot?

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You can estimate the correlation coefficient by observing the direction and tightness of the points in the scatterplot. A tighter clustering of points along a line indicates a stronger correlation.

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