By the definition of standard deviation, 95.46% of the normal population will be within 2 SD of the mean.
Explanation: The normal distribution of a population means it follows the "bell curve". The center of this bell curve is the population's mean value. One standard deviation defines two areas (on the left and right side of the central "mean" value) under the bell curve that each have 34.13% of the population. The next standard deviation adds two additional areas under the curve, each having 13.6% of the population. Adding the areas under the curves on both sides gives us (34.13% + 13.6%) x 2 = 95.46%
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.
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.
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.
I believe the standard deviations are measured from the median, not the mean.1 Standard Deviation is 34% each side of median, so that is 68% total.2 Standard Deviations is 48% each side of median, so that is 96% total.
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
0.674 sd.