(85 - 58)/11 = 27/11 = 2.4545.. sd
That depends on what the standard deviation is.
It is mean + 2*standard deviation.
Standard deviation helps you identify the relative level of variation from the mean or equation approximating the relationship in the data set. In a normal distribution 1 standard deviation left or right of the mean = 68.2% of the data 2 standard deviations left or right of the mean = 95.4% of the data 3 standard deviations left or right of the mean = 99.6% of the data
Differing from standard deviations, the coded deviation method finds the mean of grouped data from the assumed mean using unit deviations. This is a shorter way to find the mean.
In a normal distribution, approximately 95% of the data falls within 2 standard deviations of the mean. This is part of the empirical rule, which states that about 68% of the data is within 1 standard deviation, and about 99.7% is within 3 standard deviations. Therefore, the range within 2 standard deviations captures a significant majority of the data points.
2 times the standard deviation!
That depends on what the standard deviation is.
No, a standard deviation or variance does not have a negative sign. The reason for this is that the deviations from the mean are squared in the formula. Deviations are squared to get rid of signs. In Absolute mean deviation, sum of the deviations is taken ignoring the signs, but there is no justification for doing so. (deviations are not squared here)
You cannot have a standard deviation for 1 number.
No. The average of the deviations, or mean deviation, will always be zero. The standard deviation is the average squared deviation which is usually non-zero.
The mean for the WISC, like the WAIS, is 100. The deviations from 100, or standard deviations, are 15.
It is mean + 2*standard deviation.
It is the standard deviation.
The standard deviation of a set of data is a measure of the spread of the observations. It is the square root of the mean squared deviations from the mean of the data.
Standard deviations are measures of data distributions. Therefore, a single number cannot have meaningful standard deviation.
16.5 is 1 standard deviation from the mean. If you add the mean of 14 to the 1 standard deviation of 2.5, the result is 16.5.
It's used in determining how far from the standard (average) a certain item or data point happen to be. (Ie, one standard deviation; two standard deviations, etc.)