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Ok so basically the chebyshev's theorem states that 75% of your data will lie within 2 standard deviations of the mean and that 89% of your data will lie within 3 standard deviations of the mean. And I believe that this theorem is much more precise than the Empirical Rule, which assumes normality and can be off.

I am currently taking a stats. class if I didn't help or my wording is unclear please let me know. Also any information here was obtained or learned from the book called Elementary Statistics by Mario F. Triola

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Q: What is Chebyshev's theorem?
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Related questions

Will chebyshevs not work all my answers are in the negative range low value?

It would appear that you are applying Chebyshev incorrectly.


What is the difference between Chebyshevs inequality and empirical rule in terms of skweness?

See: http://wiki.answers.com/Q/What_is_the_difference_between_Chebyshevs_inequality_and_empirical_rule_in_terms_of_skewness


State the main reason for using the empirical rule rather than chebyshevs theorem?

The empirical rule can only be used for a normal distribution, so I will assume you are referring to a normal distribution. Chebyshev's theorem can be used for any distribution. The empirical rule is more accurate than Chebyshev's theorem for a normal distribution. For 2 standard deviations (sd) from the mean, the empirical rule says 95% of the data are within that, and Chebyshev's theorem says 1 - 1/2^2 = 1 - 1/4 = 3/4 or 75% of the data are within that. From the standard normal distribution chart, the answer for 2 sd from the mean is 95.44% So, as you can see the empirical rule is more accurate.


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