When the standard deviation is much less than 10 a score that is 10 points below the mean would be considered an extreme value?

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The mean and the median are both measures of central tendency that give an indication of the average value of a distribution of figures.

The mean is the average of a group of scores. The scores added up and divided by the number of scores. The mean is sensitive to extreme scores when population samples are small. For example, for a class of 20 students, if there were two students who scored well above the others, the mean will be skewed higher than the rest of the scores might indicate. Means are better used with larger sample sizes.

The median is the point at which half the scores are above and half the scores are below. Medians are less sensitive to extreme scores and are probably a better indicator generally of where the middle of the class is achieving, especially for smaller sample sizes.

The larger the population sample (number of scores) the closer mean and median become. In fact, in a perfect bell curve, the mean and median are identical.

Standard deviation

Standard deviation (SD) is a widely used measurement of variability used in statistics. It shows how much variation there is from the average (mean). A low SD indicates that the data points tend to be close to the mean, whereas a high SD indicates that the data are spread out over a large range of values.

When the standard deviation is much less than 10 a score that is 10 points below the mean would be considered an extreme value?

One SD away from the mean in either direction on the horizontal axis (the orange area on the graph) accounts for around 68 percent of the people in this group. Two SDs away from the mean (the orange and beige areas) account for roughly 95 percent of the people. And three SDs (the orange, beige and blue areas) account for about 99 percent of the people.

If this curve were flatter and more spread out, the SD would have to be larger in order to account for those 68 percent or so of the people. The SD can tell you how spread out the examples in a set are from the mean.

So if you are comparing test scores for different classes or cohorts, the SD will tell you how diverse those scores are.

For example, if you were to calculate the SD of scores from a class of students of similar ability, you would expect it to be low, because the scores would all be close to the mean. On the other hand, you would expect the SD of scores from a mixed-ability class to be higher. If these calculations did not conform to expectations, you would want to look more closely at the data to check for inaccuracies.

Standard deviations – interactive illustration

The following interactive illustrates standard deviations for two very different classes. One class has a standard deviation of 10, while the other a standard deviation of 20. Click on the buttons to see the effect this has on the spread of results.

Large/Small Standard Deviation

Please choose which graph to show.

Class A: Median = 50, StdDev = 20
68% of the students lie within one standard deviation, that is approx 2/3 of all students obtained a mark between 30 and 70%. 95% of the students lie withing 2 standard deviations and therefore obtained marks between 10 and 90%.

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Contents - Index


Tab 7: Outliers
When the standard deviation is much less than 10 a score that is 10 points below the mean would be considered an extreme value?
Tab 7 of the Test Distribution window displays any potential outliers in the data.  These points should be reviewed to see if they are in error and replaced if this is the case.  They might also represent extreme values for a long tailed distribution so transforming the data is another option.  If they cannot be eliminated and a distribution cannot be fit to the data, the use of a nonparametric tolerance interval or attribute sampling plan may be required.For each point a z-score is calculated.  The z-score is:
When the standard deviation is much less than 10 a score that is 10 points below the mean would be considered an extreme value?
A z-score of 10 means the value is 10 standard deviations above the average.  A point is marked as likely being an outlier if it is more than 10 standard deviations from the average (z-score greater than 10 or less than -10).  Robust estimates of the average and standard deviation are used for this calculation called 20% trimmed estimates.  This is so that an outlier does distinguish itself by inflating the estimate of the standard deviation.  Points that are from 4.5 to 10 standard deviations from the average are marked as either outliers relative to the normal distribution or extreme values from a long tailed distribution.The outlier shown above is from a set of data generated using the largest extreme value distribution.  Even though the one point is flagged as a potential outlier, it is in reality just part of a long tail as shown below.
When the standard deviation is much less than 10 a score that is 10 points below the mean would be considered an extreme value?
By performing a right mouse click over the graphic or clicking the Menu button, the following popup menu will appear:
When the standard deviation is much less than 10 a score that is 10 points below the mean would be considered an extreme value?
The menu items are as follows:Size To Fit:  Sizes output to fit window.  Output will shrink and expand to fit window when window is resized.Fixed Size - Normal:  Sizes output so easy to read.  If the output is too large to fit the window, scroll bars are added.Fixed Size - Custom:  Can specify the size of the output.  If the output is too large to fit the window, scroll bars are added.Print:  Prints the output.Copy to Clipboard:  Copies the output to the clipboard in Windows Meta file (Picture) format.

When the standard deviation is much less than 10 a score that is 10 points below the mean would be considered an extreme value true or false?

Therefore, a standard deviation much less than 10 would make this point an outlier. The correct answer is D) When the standard deviation is much less than 10.

Under what circumstances would a score that is 10 points above the mean be considered an extreme value or outlier?

A z-score of 10 means the value is 10 standard deviations above the average. A point is marked as likely being an outlier if it is more than 10 standard deviations from the average (z-score greater than 10 or less than -10).

What does a low standard deviation mean with test scores?

Low standard deviation means data are clustered around the mean, and high standard deviation indicates data are more spread out. A standard deviation close to zero indicates that data points are close to the mean, whereas a high or low standard deviation indicates data points are respectively above or below the mean.

How does an extreme score influence mean and standard deviation?

Describe how one extreme score influences the mean and standard deviation. The mean increased when a smaller score was replaced by a larger score. The standard deviation increased when a score close to the mean was replaced by a score farther away from the mean.