Multiply them as you would any two numbers.
However, you should note that the standard deviation of a product of two variables is not the product of their standard deviations.
That is, SD(XY) ≠SD(X)*SD(Y)
The sum of standard deviations from the mean is the error.
95% is within 2 standard deviations of the mean.
The mean for the WISC, like the WAIS, is 100. The deviations from 100, or standard deviations, are 15.
2 times the standard deviation!
Z-Score tells how many standard deviations a measurement is away from the mean.
See the related links on how to calculate standard deviation. If there are more than a dozen data points, it is tedious to calculate by hand. Use excel or an online calculator. To get 2 standard deviations, multiply the calculated std deviation by 2.
How many standard deviations is 16.50 from the mean?
The sum of standard deviations from the mean is the error.
95% is within 2 standard deviations of the mean.
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.
The mean for the WISC, like the WAIS, is 100. The deviations from 100, or standard deviations, are 15.
You can't average means with standard deviations. What are you trying to do with the two sets of data?
The z-score of a value indicates how many standard deviations it is from the mean. If a value is 2.08 standard deviations greater than the mean, its z-score is simply 2.08. This means the value lies 2.08 standard deviations above the average of the dataset.
2 times the standard deviation!
That depends on what the standard deviation is.
standard deviations
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%.