A normal distribution with a mean of 65 and a standard deviation of 2.5 would have 95% of the population being between 60 and 70, i.e. +/- two standard deviations.
95 percent of measurements are less than 2 standard deviations away from the mean, assuming a normal distribution.
if standard deviation is 4 minutes 95% probability is about 2 standard deviations (actually 1.96) so you would need to allow 30 + 8 = 38 minutes
About 98% of the population.
15/1000
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.
A normal distribution with a mean of 65 and a standard deviation of 2.5 would have 95% of the population being between 60 and 70, i.e. +/- two standard deviations.
2.576 sd
in a normal distribution, the mean plus or minus one standard deviation covers 68.2% of the data. If you use two standard deviations, then you will cover approx. 95.5%, and three will earn you 99.7% coverage
95% is within 2 standard deviations of the mean.
95 percent of measurements are less than 2 standard deviations away from the mean, assuming a normal distribution.
Percent variation is the standard deviation divided by the average
if standard deviation is 4 minutes 95% probability is about 2 standard deviations (actually 1.96) so you would need to allow 30 + 8 = 38 minutes
The answer will depend on what the distribution is. Non-statisticians often assum that the variable that they are interested in follows the Standard Normal distribution. This assumption must be justified. If that is the case then the answer is 81.9%
About 98% of the population.
Never!
I'm assuming "genius" means an unusual value (more than two standard deviations) in the right tail. This is (100 - 95.45)/2 = 2.275 percent, approximately. So: 6,575,000,000 * 0.02275 = 149,581,250 geniuses ... not that special, huh?