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Q: Is it true that the standard deviation can equal zero in a data set?

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True.

From what ive gathered standard error is how relative to the population some data is, such as how relative an answer is to men or to women. The lower the standard error the more meaningful to the population the data is. Standard deviation is how different sets of data vary between each other, sort of like the mean. * * * * * Not true! Standard deviation is a property of the whole population or distribution. Standard error applies to a sample taken from the population and is an estimate for the standard deviation.

Yes. Please see the related link, below.

a is true.

no

The true / real standard deviation ("the mean deviation from the mean so to say") which is present in the population (everyone / everything you want to describe when you draw conclusions)

If I take 10 items (a small sample) from a population and calculate the standard deviation, then I take 100 items (larger sample), and calculate the standard deviation, how will my statistics change? The smaller sample could have a higher, lower or about equal the standard deviation of the larger sample. It's also possible that the smaller sample could be, by chance, closer to the standard deviation of the population. However, A properly taken larger sample will, in general, be a more reliable estimate of the standard deviation of the population than a smaller one. There are mathematical equations to show this, that in the long run, larger samples provide better estimates. This is generally but not always true. If your population is changing as you are collecting data, then a very large sample may not be representative as it takes time to collect.

Both variance and standard deviation are measures of dispersion or variability in a set of data. They both measure how far the observations are scattered away from the mean (or average). While computing the variance, you compute the deviation of each observation from the mean, square it and sum all of the squared deviations. This somewhat exaggerates the true picure because the numbers become large when you square them. So, we take the square root of the variance (to compensate for the excess) and this is known as the standard deviation. This is why the standard deviation is more often used than variance but the standard deviation is just the square root of the variance.

I would say in America the mean IQ is about 60 and the standard deviation is about 15, this is about true for all ages.

No. You must have the mean ("average") as well.

Standard error A statistical measure of the dispersion of a set of values. The standard error provides an estimation of the extent to which the mean of a given set of scores drawn from a sample differs from the true mean score of the whole population. It should be applied only to interval-level measures. Standard deviation A measure of the dispersion of a set of data from its mean. The more spread apart the data is, the higher the deviation,is defined as follows: Standard error x sqrt(n) = Standard deviation Which means that Std Dev is bigger than Std err Also, Std Dev refers to a bigger sample, while Std err refers to a smaller sample

Yes, it is true; and the 2 quantities that describe a normal distribution are mean and standard deviation.

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