Suppose that X and Y have the following joint probability distribution:
| Y / X | -3 | 2 | 4 | Sum |
|---|---|---|---|---|
| 1 | 0.1 | 0.2 | 0.2 | 0.5 |
| 3 | 0.3 | 0.1 | 0.1 | 0.5 |
| Sum | 0.4 | 0.3 | 0.3 | 1 |
The covariance between X and Y is:
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Suppose that X and Y have the following joint probability distribution:
| Y / X | -3 | 2 | 4 | Sum |
|---|---|---|---|---|
| 1 | 0.1 | 0.2 | 0.2 | 0.5 |
| 3 | 0.3 | 0.1 | 0.1 | 0.5 |
| Sum | 0.4 | 0.3 | 0.3 | 1 |
The covariance between X and Y is:
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Suppose that X and Y have the following joint probability distribution: | Y → / X ↓ | -3 | 2 | 4 | Sum | 1 | 0.1 | 0.2 | 0.2 | 0.5 | 3 | 0.3 | 0.1 | 0.1 | 0.5 | Sum | 0.4 | 0.3 | 0.3 | 1 | The covariance between X and Y is: (A) 0 (B) 1 (C) -1 (D) -1.2
Also written as: Suppose that X and Y have the following joint probability distribution: | Y -> / X down | -3 | 2 | 4 | Sum | 1 | 0.1 | 0.2 | 0.2 | 0.5 | 3 | 0.3 | 0.1 | 0.1 | 0.5 | Sum | 0.4 | 0.3 | 0.3 | 1 | The covariance between X and Y is:
Joint distributions, covariance and correlation has come up 61 times in 7 exams since 2005.
This question is on Covariance and its properties, part of Joint distributions, covariance and correlation in Statistics.
How two variables move together and how covariance combines.
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Question from the JNU SIS 2021 paper. Solutions are TestStop's own. Not affiliated with or endorsed by any examination authority.