Chebyshev's theorem, also known as Chebyshev's inequality, provides a certain amount of certainty about the distribution of data in a population. The theorem states that no matter the shape of the data set, at least 1 - 1/k^2 of the data must fall within k standard deviations from the mean.

Here, k=3. So, we substitute k=3 into the formula:

1 - 1/k^2 = 1 - 1/3^2 = 1 - 1/9 = 8/9 = 0.888...

So, Chebyshev's rule suggests that at least 88.8% (approximately 89%) of the data distribution is around the mean when k=3.

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Chebyshev's theorem, also known as Chebyshev's inequality, provides a certain amount of certainty about the distribution of data in a population. The theorem states that no matter the shape of the data set, at least 1 - 1/k^2 of the data must fall within k standard deviations from the mean.

Here, k=3. So, we substitute k=3 into the formula:

1 - 1/k^2 = 1 - 1/3^2 = 1 - 1/9 = 8/9 = 0.888...

So, Chebyshev's rule suggests that at least 88.8% (approximately 89%) of the data distribution is around the mean when k=3.

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Chebyshev's theorem, also known as Chebyshev's inequality, provides a certain amount of certainty about the distribution of data in a population. The theorem states that no matter the shape of the data set, at least 1 - 1/k^2 of the data must fall within k standard deviations from the mean.

Here, k=3. So, we substitute k=3 into the formula:

1 - 1/k^2 = 1 - 1/3^2 = 1 - 1/9 = 8/9 = 0.888...

So, Chebyshev's rule suggests that at least 88.8% (approximately 89%) of the data distribution is around the mean when k=3.

Chebeshev rule suggest atleast___________% distribution of data around mean while K=3.Group of answer choices89759995

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