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The standard deviation is a measure of how much variation there is in a data set. It can be zero only if all the values are exactly the same - no variation.

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โˆ™ 2009-11-07 16:55:44
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A polynomial of degree zero is a constant term

The grouping method of factoring can still be used when only some of the terms share a common factor A True B False

The sum or difference of p and q is the of the x-term in the trinomial

A number a power of a variable or a product of the two is a monomial while a polynomial is the of monomials

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Q: Is it true that the standard deviation can equal zero in a data set?
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True or false a distribution of sample means is normally distributed with a mean equal to the population mean and standard deviation equal to the standard error of the mean?


Is standard deviation same as standard error?

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.

Is it true that the standard deviation is equal to the square root of the variance?

Yes. Please see the related link, below.

What is true of a standard normal probability distribution aA mean of 0 and a standard deviation of 1 b A mean of 1 and any standard deviation of 1 c Any mean and a standard deviatio?

a is true.

Is it true that the larger the standard deviation the wider the confidence interval?


What is a population standard deviation?

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)

How does a sample size impact the standard deviation?

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.

Why standard deviation is more often used than variance?

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.

What is the standard deviation of kids in a family in America in any or all of the last 5 years?

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.

Is it true that normal distribution is characterised by Standard deviation only?

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

What is the difference between standard error of sample mean and sample standard deviation?

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

Are these true of normal probability distribution IIt is symmetric about the mean TTotal area under the normal distribution curve is equal to 1 DDistribution is totally described by two quantities?

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

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