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Standard deviation is basically how much your scores vary from the mean or average score. So if you have a mean of 5 and a standard deviation of 2 it indicates that most of your values are around 5, and if they are not they will usually be +/- 2 units different (between 3 and 7). If you have a large standard deviation it simply means that your data includes a wide range of values. In some cases it may mean that you have an outlier, or an error in your data, in other cases it is normal depending on what you are measuring.
For example if you are taking a sample of peoples ages and you get a mean of 50 and a standard deviation of 20 that would be normal because you can expect ages to range from 0-100. But if you are measuring shoe size and you get a mean of 8 and a standard deviation of 6 you can expect that something is wrong with your data because not many people have size 2 or size 14 shoes.
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Is the standard deviation best thought of as the distance from the mean?
No. A small standard deviation with a large mean will yield points further from the mean than a large standard deviation of a small mean. Standard deviation is best thought of as spread or dispersion.
In research how to define standard deviation?
Standard deviation shows how much variation there is from the "average" (mean). A low standard deviation indicates that the data points tend to be very close to the mean, whereas high standard deviation indicates that the data are spread out over a large range of values.
What are the assumptions of standard deviation?
The standard deviation is the standard deviation! Its calculation requires no assumption.
What combination of factors will produce the smallest value for the standard error?
A small sample and a large standard deviation
What is the difference between standard error of mean and standard deviation of means?
Standard error of the mean (SEM) and standard deviation of the mean is the same thing. However, standard deviation is not the same as the SEM. To obtain SEM from the standard deviation, divide the standard deviation by the square root of the sample size.
