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That there is quite a large amount of variation between the observations.

Q: What does large standard deviation signify?

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A standard deviation in statistics is the amount at which a large number of given values in a set might deviate from the average. A percentile deviation represents this deviation as a percentage of the range.

that you have a large variance in the population and/or your sample size is too small

The standard deviation of the population. the standard deviation of the population.

The standard deviation is 0.

It shows primarily that the measurement unit used for recording the data is very large. For example, the standard deviation of the heights of individuals, when recorded in metres, will be one hundredth of the standard deviation of their heights when recorded in centimetres. The process is known as coding.

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A small standard deviation indicates that the data points in a dataset are close to the mean or average value. This suggests that the data is less spread out and more consistent, with less variability among the values. A small standard deviation may indicate that the data points are clustered around 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.

A large standard deviation means that the data were spread out. It is relative whether or not you consider a standard deviation to be "large" or not, but a larger standard deviation always means that the data is more spread out than a smaller one. For example, if the mean was 60, and the standard deviation was 1, then this is a small standard deviation. The data is not spread out and a score of 74 or 43 would be highly unlikely, almost impossible. However, if the mean was 60 and the standard deviation was 20, then this would be a large standard deviation. The data is spread out more and a score of 74 or 43 wouldn't be odd or unusual at all.

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.

If I have understood the question correctly, despite your challenging spelling, the standard deviation is the square root of the average of the squared deviations while the mean absolute deviation is the average of the deviation. One consequence of this difference is that a large deviation affects the standard deviation more than it affects the mean absolute deviation.

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.

A standard deviation in statistics is the amount at which a large number of given values in a set might deviate from the average. A percentile deviation represents this deviation as a percentage of the range.

Standard deviation can be calculated using non-normal data, but isn't advised. You'll get abnormal results as the data isn't properly sorted, and the standard deviation will have a large window of accuracy.

The standard deviation is the standard deviation! Its calculation requires no assumption.

that you have a large variance in the population and/or your sample size is too small

The standard deviation of the population. the standard deviation of the population.

A small sample and a large standard deviation