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Would a small deviation in an experiment mean that something is wrong with the experiment?
Not necessarily. It might mean that the experiment has a highly stable outcome. You need to evaluate if that is true or if the experiment is flawed. It comes down to theoretical expectations versus experimental outcomes - you should know a priori (before the fact) what to expect, so you can know if the results are good.
For instance...
If you were measuring the radioactivity of a sample with a relatively low count rate using a detector that recorded counts in each second, you would expect a poissen distribution.
If you were measuring the same sample with a detector that counted for 1 minute, you would expect a more gaussian distribution.
If, on the other hand, you were measuring the wavelength of a red laser, you would expect that every single observation would give you the same results, within an extremely tight distribution.
What else can I help you with?
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.
What is the difference between deviation and variation?
Deviation = A full change from the Original (depending on what you're deviating from), while Variation = a change of small or fairly insignificant magnitude from the Original.
What combination of factors will produce the smallest value for the standard error?
A small sample and a large standard deviation
What can be said about a set of data when its standard deviation is small but not zero?
This means that the set of data is clustered really close to the mean/average. Your data set likely has a small range (highest value - lowest value). In other words, if the average is 6.3, and the standard deviation is 0.7, this means that each individual piece of data, on average, is different from the mean by 0.7. Each piece of data deviates from the mean by an average (standard) of 0.7; hence standard deviation! By definition, 66% of all data is 1 standard deviation from the mean, so 66% of the data in this example would be between the values of 5.6 and 7.0.
What is the relationship between the relative size of the starndard deviation and the kurtosis of a distribution?
It is inversely proportional; a larger standard deviation produces a small kurtosis (smaller peak, more spread out data) and a smaller standard deviation produces a larger kurtosis (larger peak, data more centrally located).
If the standard deviation is small the data is more dispersed?
No, if the standard deviation is small the data is less dispersed.
Square of the deviation will be less if?
If the deviation is small ie if the distribution is packed close to the mean.
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.
What was aunt Harriet's baby's deviation in The Chrysalids?
The book never gives us this information. It is apparently something small from the way Harriet talks about it.
What a large standard deviation means?
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.
Where the standard deviation is not applicable?
When the sample size is small
What does standard deviation show us about a set of scores?
Standard Deviation tells you how spread out the set of scores are with respects to the mean. It measures the variability of the data. A small standard deviation implies that the data is close to the mean/average (+ or - a small range); the larger the standard deviation the more dispersed the data is from the mean.
Can standard deviation equal zero?
Standard deviation can only be zero if all the data points in your set are equal. If all data points are equal, there is no deviation. For example, if all the participants in a survey coincidentally were all 30 years old, then the value of age would be 30 with no deviation. Thus, there would also be no standard deviation.A data set of one point (small sample) will always have a standard deviation of zero, because the one value doesn't deviate from itself at all.!
What does small standard deviation signify?
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.
What if your small intestine is how long?
A normal small intestine is 17 feet with an absolute deviation of about three to four feet.
What is the difference between deviation and variation?
Deviation = A full change from the Original (depending on what you're deviating from), while Variation = a change of small or fairly insignificant magnitude from the Original.
When comparing electrical usage among customer a small standard deviation indicates that the mean is?
It doesn't matter whether comparisons are involved. A small standard deviation indicates that population values are likely to be clustered closely around the mean.
