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Q: Is the standard error of the sample mean assesses the uncertainty or error of estimation?
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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 is point estimation?

In statistics, point estimation is the process of providing a number or vector (which could be an infinite dimensional vector such as a function) that is stochastically 'close' in some sense to the actual value of that number or vector. For example, suppose that a population of people has a known mean height of 180 cm and an unknown standard deviation. Point estimation could be applied to a sample from this population to obtain an estimate of the standard deviation of its heights.


Why is it good to have a high sample size?

It increases the accuracy of the estimation and reduces the associated error range.


What is the sample size for standard deviation?

There is no such thing. The standard error can be calculated for a sample of any size greater than 1.


Can a standard deviation of a sample be equal to a standard deviation of a population?

Yes

Related questions

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.


Does a Quota Sample represent the whole population?

yes because the quota sample include the random sample and when we have over estimation we will use the quota sample


What is point estimation?

In statistics, point estimation is the process of providing a number or vector (which could be an infinite dimensional vector such as a function) that is stochastically 'close' in some sense to the actual value of that number or vector. For example, suppose that a population of people has a known mean height of 180 cm and an unknown standard deviation. Point estimation could be applied to a sample from this population to obtain an estimate of the standard deviation of its heights.


How does one calculate the standard error of the sample mean?

Standard error of the sample mean is calculated dividing the the sample estimate of population standard deviation ("sample standard deviation") by the square root of sample size.


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


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.


What are Prerequisites for collection of blood sample for serum calcium level estimation?

Do not use tourniquet


What is the sample standard deviation of 27.5?

A single observation cannot have a sample standard deviation.


Why is it good to have a high sample size?

It increases the accuracy of the estimation and reduces the associated error range.


How does sample size affect the size of your standard error?

The standard error should decrease as the sample size increases. For larger samples, the standard error is inversely proportional to the square root of the sample size.The standard error should decrease as the sample size increases. For larger samples, the standard error is inversely proportional to the square root of the sample size.The standard error should decrease as the sample size increases. For larger samples, the standard error is inversely proportional to the square root of the sample size.The standard error should decrease as the sample size increases. For larger samples, the standard error is inversely proportional to the square root of the sample size.


How do i find sample standard deviation from population standard deviation?

If the population standard deviation is sigma, then the estimate for the sample standard error for a sample of size n, is s = sigma*sqrt[n/(n-1)]


What is the value of the standard error of the sample mean?

The sample standard deviation (s) divided by the square root of the number of observations in the sample (n).