Examples of using Three standard deviations in English and their translations into Indonesian
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Ecclesiastic
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Ecclesiastic
Three standard deviations include about 99% of all observations.
And 99.7% of all data points will be within three standard deviations of the population average.
And three standard deviations(between the dotted lines) account for about 99 percent of the people.
Furthermore it would trade between $20 and $80- three standard deviations- 99% of the time.
The fatter tailsincrease the probability that an investment will move beyond three standard deviations.
Severe microcephaly is defined as a head circumference less than three standard deviations(3SDs) below the average for babies of the same age and sex.
Assume that four of these trials are within 0.1 seconds of each other, but the fifth trial differs from these by 1.4 seconds i.e.,more than three standard deviations away from Node.
Meanwhile, abnormality is the statistical rarity, falling in between two and three standard deviations away above or below the average, which is 4.3% of the population.
People with early-onset obesity which is an onset before 10 years of age andbody mass index over three standard deviations above normal.
Normally you would look at how far the price is from the mean,e.g. does the price fall two or three standard deviations away from the mean or some other technical indicator like the Average True Range(an exponential moving average of the True Range), some support level, another security, etc.
Finally, there is a 99.7% likelihood that the sample will fall within three standard deviations of the mean.
In contrast, a different trader with greaterappetite for risk may objectively decide that three standard deviations from the norm(i.e. 99.7%) is the appropriate certainty level for judging a trading system as“failed.”.
It will end up within two standard deviations 95% of the time and within three standard deviations 99% of the time.
Ninety-five percent of the measurements will be within two standard deviations, 99% within three standard deviations, etc., but we never expect 100% of the measurements to overlap within any finite-sized error.
As a rule ofthumb, unless there is a physical explanation of why the suspect value is spurious and it is no more than three standard deviations away from the expected.
Ninety-five percent of the measurements will be within two standard deviations, 99% within three standard deviations, etc., but we never expect 100% of the measurements to overlap within any finite-sized error for a truly Gaussian distribution.
With a, the tails of measuredvalues may extend well beyond plus and minus three standard deviations from the process average.
Furthermore, these numbers would imply that the S&P500 is currently trading at almost three standard deviations away from its mean, which for many distribution is a highly improbable event.
As a rule ofthumb, unless there is a physical explanation of why the suspect value is spurious and it is no more than three standard deviations away from the expected value, it should probably be kept.
As a rule of thumb,unless there is a physical explanation of why the suspect value is spurious and it is no more than three standard deviations away from the expected Thus it is necessary to quantify random errors by means of statistical analysis.
In children with early-onset severe obesity(defined by an onset before ten years of age andbody mass index over three standard deviations above normal), 7% harbor a single locus mutation.
In people with early-onset severe obesity(defined by an onset before 10 years of age andBMI over three standard deviations above the value for normal individual age-and sex-match), 7% harbor a single point DNA mutation.
Moving two standard deviations away from the mean should include 95% of the 100 test scores collected,and moving three standard deviations away from the mean should represent 99.7% of the 100 test scores.
Given a standard deviation of 5 pixels, only 0.3% of the monkey heights will be less than 235 pixels(three standard deviations below the mean of 250) or greater than 265 pixels(three standard deviations above the mean of 250).
Nearly all(99.7%) of the data falls within three standard deviation distances from the mean.
Any test scores that are extreme outliers, such as a score of 100 or 0,would be considered long-tail data points and lie outside of the three standard deviation range.
