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For data sets having a normal, bell-shaped distribution, the following properties apply: About 68% of all values fall within 1 standard deviation of the mean About 95% of all values fall within 2 standard deviation of the mean About 99.7% of all values fall within 3 standard deviation of the mean.

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Q: A What is empirical rule?
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What does the Empirical Rule indicate?

An empirical rule indicates a probability distribution function for a variable which is based on repeated trials.


Can the Empirical Rule of probability be applied to the uniform probability distribution?

Yes, except that if you know that the distribution is uniform there is little point in using the empirical rule.


Does the empirical rule work for any data set?

No.The empirical rule is a good estimate of the spread of the data given the mean and standard deviation of a data set that follows the normal distribution.If you you have a data set with 10 values, perhaps all 10 the same, you clearly cannot use the empirical rule.


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.


In the Empirical Rule of data will fall in with two standard deviation.?

Approx 95% of the observations.


What is the empirical rule for 1 and 2 standard deviations?

The empirical rule is 68 - 95 - 99.7. 68% is the area for +/- 1 standard deviation (SD) from the mean, 95% is the area for +/- 2 SD from the mean; and 99.7% is the area for +/- 3 SD from the mean.


How does the bell curve relates to the empirical rule?

The bell curve, also known as the normal distribution, is a symmetrical probability distribution that follows the empirical rule. The empirical rule states that for approximately 68% of the data, it lies within one standard deviation of the mean, 95% within two standard deviations, and 99.7% within three standard deviations when data follows a normal distribution. This relationship allows us to make predictions about data distribution based on these rules.


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


By the empirical rule what percentage of the area under the normal curve lies to the left of mu the average Put your answer as a percentage?

50%


Is Empirical Rule when 75 percent of the observations lie within plus and minus 2.00 average mean deviations?

me la pelas


The Empirical Rule indicates that we can expect to find what proportion of the sample included within plus or and - 2 standard deviation?

The proportion is approx 95%.


What is the probability found by experimenting?

It is experimental or empirical probability.It is experimental or empirical probability.It is experimental or empirical probability.It is experimental or empirical probability.