0
If the Mean equals 100 variance equals 40 and sample size equals 10 what is the standard deviation?
Wiki User
∙ 14y ago
6.3
Wiki User
∙ 14y ago
Add your answer:
Earn +20 pts
What does it means if the standard deviation is large?
that you have a large variance in the population and/or your sample size is too small
What is not dependent on the size of a sample?
In general the mean of a truly random sample is not dependent on the size of a sample. By inference, then, so is the variance and the standard deviation.
Why is standard deviation a better measure of dispersion than variance?
Because it is in same units as the original data. For example, if you have a sample of lengths, all in centimetres, the sample variance will be in units of centrimetres2 which might be more difficult to interpret but the sample standard deviation with be in units of centimetres, which would be relatively easy to intepret with reference to the data.
What does n-1 indicate in a calculation for variance?
The n-1 indicates that the calculation is being expanded from a sample of a population to the entire population. Bessel's correction(the use of n − 1 instead of n in the formula) is where n is the number of observations in a sample: it corrects the bias in the estimation of the population variance, and some (but not all) of the bias in the estimation of the population standard deviation. That is, when estimating the population variance and standard deviation from a sample when the population mean is unknown, the sample variance is a biased estimator of the population variance, and systematically underestimates it.
What sample size is needed to disprove the hypothesis that the probability of outcome A equals 0.25?
The answer depends on what population characteristic A measures: whether it is mean, variance, standard deviation, proportion etc. It also depends on the sampling distribution of A.
The standard deviation of a sample of 10000 observations equals 121 The variance of the sample equals?
It equals 14641.
What is the relationship between standard deviation and variance for the same sample data?
The standard deviation is the square root of the variance.
Variance and standard deviation are one and the same thing?
No. But they are related. If a sample of size n is taken, a standard deviation can be calculated. This is usually denoted as "s" however some textbooks will use the symbol, sigma. The standard deviation of a sample is usually used to estimate the standard deviation of the population. In this case, we use n-1 in the denomimator of the equation. The variance of the sample is the square of the sample's standard deviation. In many textbooks it is denoted as s2. In denoting the standard deviation and variance of populations, the symbols sigma and sigma2 should be used. One last note. We use standard deviations in describing uncertainty as it's easier to understand. If our measurements are in days, then the standard deviation will also be in days. The variance will be in units of days2.
If the variance of the data values in a sample is 121 what is the standard deviation of the data values?
11
If the variance of the data values in a sample is 169 what is the standard deviation of the data values?
For a sample, the SD is 13.53, approx.
What does it means if the standard deviation is large?
that you have a large variance in the population and/or your sample size is too small
What is not dependent on the size of a sample?
In general the mean of a truly random sample is not dependent on the size of a sample. By inference, then, so is the variance and the standard deviation.
Why is standard deviation a better measure of dispersion than variance?
Because it is in same units as the original data. For example, if you have a sample of lengths, all in centimetres, the sample variance will be in units of centrimetres2 which might be more difficult to interpret but the sample standard deviation with be in units of centimetres, which would be relatively easy to intepret with reference to the data.
What does n-1 indicate in a calculation for variance?
The n-1 indicates that the calculation is being expanded from a sample of a population to the entire population. Bessel's correction(the use of n − 1 instead of n in the formula) is where n is the number of observations in a sample: it corrects the bias in the estimation of the population variance, and some (but not all) of the bias in the estimation of the population standard deviation. That is, when estimating the population variance and standard deviation from a sample when the population mean is unknown, the sample variance is a biased estimator of the population variance, and systematically underestimates it.
How much error between sample mean and population mean?
The answer depends on the underlying variance (standard deviation) in the population, the size of the sample and the procedure used to select the sample.
Is sample standard deviation the same as standard deviation?
No, the standard deviation is a measure of the entire population. The sample standard deviation is an unbiased estimator of the population. It is different in notation and is written as 's' as opposed to the greek letter sigma. Mathematically the difference is a factor of n/(n-1) in the variance of the sample. As you can see the value is greater than 1 so it will increase the value you get for your sample mean. Essentially, this covers for the fact that you are unlikely to obtain the full population variation when you sample.
Standard deviation considered a crude measure of variance?
No. Well not exactly. The square of the standard deviation of a sample, when squared (s2) is an unbiased estimate of the variance of the population. I would not call it crude, but just an estimate. An estimate is an approximate value of the parameter of the population you would like to know (estimand) which in this case is the variance.
