Examples of 'sample variance' in a sentence
Meaning of "sample variance"
Sample variance: In statistics, sample variance is a measure of how spread out a set of data points are around the mean. It is used to quantify the dispersion or variability of a sample dataset
How to use "sample variance" in a sentence
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sample variance
And we are going to calculate the unbiased sample variance.
The sample variance is an estimate of the population variance.
Population variance and sample variance.
Sample mean and sample variance and their numerical characteristics.
So we are going to calculate the unbiased sample variance.
So this is sample variance.
Difference between population variance and sample variance.
Unbiased sample variance.
Examples include the sample mean and sample variance.
The sample variance is.
Equals the square root of the sample variance.
Where the weighted sample variance of the vector e of price deviations is defined as.
Distribution of the sample variance.
In this case, the sample variance is a biased estimator of the population variance.
Or the unbiased sample variance.
See also
The differences between the estimates variation are caused by variations between studies sample variance.
This is a simple example of how to calculate sample variance and sample standard deviation.
The first expression in this formula is most suitable for interpreting the sample variance.
Joint distribution of sample mean and sample variance for sample from normal distribution.
Explaining the difference between population variance and sample variance.
Independence of sample mean and sample variance of a normal distribution ( known variance ).
Let us get the calculator out to actually figure out our sample variance.
In other words, the sample variance is an unbiased estimate of the population variances.
Actually this is what some people often refer to when they talk about sample variance.
As a result, the effect of sample to sample variance on nested amplification results is diminished.
A well-known example arises in the estimation of the population variance by sample variance.
Q, How to find the sample variance and standard deviation.
Remember, we want the unbiased sample variance.
All of the sample variance distances, right?
Now, that gave us our unbiased sample variance.
The sample variance is equal to 4.
Log-normal distribution provided the best results, however underestimated the sample variance.
Weighting by reciprocal of within-concentration sample variance is not recommended Bunke et al.
Plus my sample standard deviation for the control squared, which is the sample variance.
Returns the sample variance ( allowing text and logical values ).
The variation among licenses ( fishers ) accounts for most of the remaining sample variance.
For non-normal data, the distribution of the sample variance may deviate substantially from a χ2 distribution.
Instead, a re-sampling approach known as the bootstrap method is used to approximate the sample variance.
Where sx2 is the sample variance.
Statistical Analysis . One-tailed Student 's t-test assuming unequal sample variance was used.
S2 observed value of the sample variance.
Those three factors explained 72 % of the total sample variance.
Now we get to the interesting part, Sample variance.
Note that if all data points are identical, then the sample variance is 0.
So I could say -- And this is actually a sample variance.
And the quantity s2 ( xi ) is called the sample variance.
Well, the logic, I guess, is reasonable to say, well, this is our unbiased sample variance.
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