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.
If you are talking about the z-value of a point on the normal curve, then no, it is 1.5 standard deviations BELOW the mean.
95%
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%
95
s= bracket n over sigma i (xi-x-)^2 all over n-1 closed bracket ^ 1/2
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.
In a normal distribution, approximately 68% of the population falls within one standard deviation of the mean, and about 95% falls within two standard deviations. Therefore, to find the percentage of the population between one standard deviation below the mean and two standard deviations above the mean, you would calculate 95% (within two standard deviations) minus 34% (the portion below one standard deviation), resulting in approximately 61% of the population.
2.275 %
All minor deviations occurring with two standard deviations under the Gaussian curve are considered normal. Deviations occurring outside of two standard deviations are considered abnormal.
It depends on the shape of the distribution. For standard normal distribution, a two tailed range would be from -1.15 sd to + 1.15 sd.
In a normal distribution, approximately 68% of scores fall within one standard deviation of the mean (between -1 and +1 standard deviations). About 95% of scores fall within two standard deviations (between -2 and +2 standard deviations). Therefore, the percentage of scores that falls specifically between the mean and -2 to 2 standard deviations is about 95% minus the 50% that is below the mean, resulting in approximately 45%.
Approximately 2 standard deviations (1.96, actually) from the mean. That is important to know that if one has a sample of 1000 values, if one selects a threshold at +/- 2 standard deviations from the mean, then one expects to see about 25 values exceeding those thresholds (on each side of the mean)
99.7% of scores fall within -3 and plus 3 standard deviations around the mean in a normal distribution.
Nearly all the values in a sample from a normal population will lie within three standard deviations of the mean. Please see the link.
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.
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