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.
Well I tink you mean the duet rule appling to first period and octet rule. The octet rule relates to the stable configuration that atoms can achive by sharing electrons, and is the outer shell of the noble gases. HOWEVER for period 3 and above atoms can hold more than 8 electrons in their outermost shells.
The phase rule is a principle in physical chemistry that relates the number of phases, components, and degrees of freedom in a system at equilibrium. It helps to predict the number of coexisting phases in a system based on its degrees of freedom and components.
Authoritarian Rule
octet rule
This rule doesn't exist; you think probable to octet rule.
50%
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.
An empirical rule indicates a probability distribution function for a variable which is based on repeated trials.
Yes, except that if you know that the distribution is uniform there is little point in using the empirical rule.
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?
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?
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.
-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.
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.
government
locus curve
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.