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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.

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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%


What percent of a normal population is within 2 standard deviations of the mean?

In a normal distribution, approximately 95% of the population falls within 2 standard deviations of the mean. This is known as the 95% rule or the empirical rule. The empirical rule states that within one standard deviation of the mean, about 68% of the population falls, and within two standard deviations, about 95% of the population falls.


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.


How to use the Empirical Rule to estimate the proportion of costs within two standard deviations of the mean?

IQ scores for adult students age 25-45 have a bell-shaped distribution with a mean of 100 and a standard deviation of 15.sing the Empirical Rule, what percentage of adult students age 25-45 have IQ scores between 70 and 130?


How can you find the percentage of empirical rule?

The number of potholes inThe number of potholes in any given 1 mile stretch of freeway pavement in Pennsylvania has a bell-shaped distribution. This distribution has a mean of 61 and a standard deviation of 9. Using the empirical rule (as presented in the book), what is the approximate percentage of 1-mile long roadways with potholes numbering between 34 and 70? any given 1 mile stretch of freeway pavement in Pennsylvania has a bell-shaped distribution. This distribution has a mean of 61 and a standard deviation of 9. Using the empirical rule (as presented in the book), what is the approximate percentage of 1-mile long roadways with potholes numbering between 34 and 70?


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.


What are the Theoretical properties of normal distribution?

-It is symmetrical (mean = median) -It is bell shaped (empirical rule applies) -The interquartile range equals 1.33 standard deviations -The range is appr. equal to 6 stand. dev.


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

Chebyshev's inequality: The fraction of any data set lying within K standard deviations is always at least 1-1/K^2 where K is any positive number greater than 1. It does not assume that any distribution. Now, there is the empirical rule of bell shaped curves or the 68-95-99.7 rule, which states that for a bell shaped curve: 68% of all values should fall within 1 standard deviation, 95% of all values should fall within 2 standard deviations and 99.7% of all values should fall within 3 standard deviation. If we suspect that our data is not bell shaped, but right or left skewed, the above rule can not be applied. I note that one test of skewness is Pearson's index of skewness, I= 3(mean of data - median of data)/(std deviation) If I is greater or equal to 1000 or I is less than 1, the data can be considered significantly skewed. I hope this answers your question. I used the textbook Elementary Statistics by Triola for the information on Pearson's index. If this answer is insufficient, please resubmit and be a bit more definitive on what you mean by empirical rule.


What is the rule of law as it relates to the federal government?

government


What is a curve formed by a point which moves according to a mathematically defined rule called?

locus curve


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.