The answer depends on what the standard deviation is.
This is 3 standard deviations above and below the mean.
It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.
The 68-95-99.7 rule states that in a normally distributed set of data, approximately 68% of all observations lie within one standard deviation either side of the mean, 95% lie within two standard deviations and 99.7% lie within three standard deviations.Or looking at it cumulatively:0.15% of the data lie below the mean minus three standard deviations2.5% of the data lie below the mean minus two standard deviations16% of the data lie below the mean minus one standard deviation50 % of the data lie below the mean84 % of the data lie below the mean plus one standard deviation97.5% of the data lie below the mean plus two standard deviations99.85% of the data lie below the mean plus three standard deviationsA normally distributed set of data with mean 100 and standard deviation of 20 means that a score of 140 lies two standard deviations above the mean. Hence approximately 97.5% of all observations are less than 140.
Well, the average I.Q. is 100, so you're slightly below average. You would still be considered average, though. Deviations of ±5 on IQ scores are considered statistically insignificant, a retest could easily be higher as you might be more relaxed the second time.
If the process can be assumed to follow a Gaussian distribution then 99.7% of the outputs of the process will lie between those two limits. That may be of benefit in quality control if it is a production process.
This is 3 standard deviations above and below the mean.
This is almost 2 standard deviations below average so these numbers indicate a person who will be challenged when it comes to learning academic material.
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.
2.576 sd
Above 1.96: 0.024998 = 2.5% below 1.96: 0.975002 = 97.5%
z-score of a value=(that value minus the mean)/(standard deviation). So a z-score of -1.5 means that a value is 1.5 standard deviations below the mean.
It means below the expected standard, or below average
The "z-score" is derived by subtracting the population mean from the measurement and dividing by the population standard deviation. It measures how many standard deviations the measurement is above or below the mean. If the population mean and standard deviation are unknown the "t-distribution" can be used instead using the sample mean and sample deviation.
It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.
In general, and assuming a reported mean of 100 and an SD of 15 for the PPV norm groups, a score of 80 is 1.3 standard deviations below the mean. It is not the worst possible score, but it does represent a significant deviation from the average performance.
The 68-95-99.7 rule states that in a normally distributed set of data, approximately 68% of all observations lie within one standard deviation either side of the mean, 95% lie within two standard deviations and 99.7% lie within three standard deviations.Or looking at it cumulatively:0.15% of the data lie below the mean minus three standard deviations2.5% of the data lie below the mean minus two standard deviations16% of the data lie below the mean minus one standard deviation50 % of the data lie below the mean84 % of the data lie below the mean plus one standard deviation97.5% of the data lie below the mean plus two standard deviations99.85% of the data lie below the mean plus three standard deviationsA normally distributed set of data with mean 100 and standard deviation of 20 means that a score of 140 lies two standard deviations above the mean. Hence approximately 97.5% of all observations are less than 140.
The variances are squared so that all deviations above and below the mean become positive values. Taking the square root of the variance then gives a measure of the differences from the mean: the standard deviaton. Squaring the deviations also makes the bigger differences stand out. Look at 100 squared vs 10 squared.