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is their sample variance, then

by Stephen B. Vardeman, Joanne Wendelberger, S Yi, Yi Yy , 2003
"... There is a little-known but very simple generalization of the standard result that for uncorrelated variables with a common mean and variance, the expected sample variance is the marginal variance. The generalization justifies the use of the usual standard error of the sample mean in possibly hetero ..."
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There is a little-known but very simple generalization of the standard result that for uncorrelated variables with a common mean and variance, the expected sample variance is the marginal variance. The generalization justifies the use of the usual standard error of the sample mean in possibly

Estimation of sampling variance

by Eugenio J. Gonzalez, Pierre Foy, Eugenio J. Gonzalez, Pierre Foy , 2000
"... To obtain estimates of student proficiency in mathematics and science that were both accurate and cost-effective, TIMSS 1999 made extensive use of probability sampling techniques to sample students from national student populations. 1 Statistics computed from these national probability samples were ..."
Abstract - Cited by 4 (1 self) - Add to MetaCart
To obtain estimates of student proficiency in mathematics and science that were both accurate and cost-effective, TIMSS 1999 made extensive use of probability sampling techniques to sample students from national student populations. 1 Statistics computed from these national probability samples were

Approximation Of Sampling variances and confidence intervals . . .

by K. Meyer, W. G. Hill
"... After reviewing pertinent literature on the estimation of sampling variances and confidence intervals in the maximum likelihood framework, a method to approximate these for individual parameters in a multi-parameter analysis is described. It is based on the profile likelihood, defined as the likelih ..."
Abstract - Cited by 9 (2 self) - Add to MetaCart
After reviewing pertinent literature on the estimation of sampling variances and confidence intervals in the maximum likelihood framework, a method to approximate these for individual parameters in a multi-parameter analysis is described. It is based on the profile likelihood, defined

Continuous Record Asymptotics for Rolling Sample Variance Estimators

by Dean Foster, Dan Nelson - Econometrica , 1996
"... It is widely known that conditional covariances of asset returns change over time. ..."
Abstract - Cited by 127 (0 self) - Add to MetaCart
It is widely known that conditional covariances of asset returns change over time.

Total variance as an exact analysis of the sample variance

by Donald B. Percival, David A. Howe - Proc. 29th Ann. PTTI Systems and Applications Meeting , 1997
"... Given a sequence of fractional frequency deviates, we investigate the relationship between the sample variance of these deviates and the total variance (Totvar) estimator of the Allan variance. We demonstrate that we can recover exactly twice the sample variance by renormalizing the Totvar estimator ..."
Abstract - Cited by 4 (2 self) - Add to MetaCart
Given a sequence of fractional frequency deviates, we investigate the relationship between the sample variance of these deviates and the total variance (Totvar) estimator of the Allan variance. We demonstrate that we can recover exactly twice the sample variance by renormalizing the Totvar

1 On Some Representations of Sample Variance*

by Anwar H Joarder
"... The usual formula of variance depending on the rounding off the sample mean lacks in precision especially when computer programs are used for the calculation. The well known simplification of the total sums of squares does not always benefit. Since the variance of two observations is easily calculat ..."
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The usual formula of variance depending on the rounding off the sample mean lacks in precision especially when computer programs are used for the calculation. The well known simplification of the total sums of squares does not always benefit. Since the variance of two observations is easily

Simple Approximations to Null Sampling Variances

by Robert H. Somers
"... Procedures for significance testing and confidence interval estimation of several employed measures of association have been available for several years, but rarely used, possibly because of the lengthy computations entailed. Simple formulas involving the sample size and the number of rows and colum ..."
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Procedures for significance testing and confidence interval estimation of several employed measures of association have been available for several years, but rarely used, possibly because of the lengthy computations entailed. Simple formulas involving the sample size and the number of rows

Exact Bounds on Sample Variance of Interval Data

by Scott Ferson, Lev Ginzburg Vladik Kreinovich, Lev Ginzburg, Vladik Kreinovich, Monica Aviles , 2002
"... We provide a feasible (quadratic time) algorithm for computing the lower bound V on the sample variance of interval data. The problem of computing the upper bound V is, in general, NP-hard. We provide a feasible algorithm that computes V for many reasonable situations. ..."
Abstract - Cited by 11 (9 self) - Add to MetaCart
We provide a feasible (quadratic time) algorithm for computing the lower bound V on the sample variance of interval data. The problem of computing the upper bound V is, in general, NP-hard. We provide a feasible algorithm that computes V for many reasonable situations.

Empirical Bernstein Bounds and Sample Variance Penalization

by Andreas Maurer, Massimiliano Pontil
"... We give improved constants for data dependent and variance sensitive confidence bounds, called empirical Bernstein bounds, and extend these inequalities to hold uniformly over classes of functions whose growth function is polynomial in the sample size n. The bounds lead us to consider sample varianc ..."
Abstract - Cited by 15 (0 self) - Add to MetaCart
We give improved constants for data dependent and variance sensitive confidence bounds, called empirical Bernstein bounds, and extend these inequalities to hold uniformly over classes of functions whose growth function is polynomial in the sample size n. The bounds lead us to consider sample

I. RELATIONSHIP BETWEEN SAMPLE MEAN AND SAMPLE VARIANCE

by unknown authors
"... Abstract. The problem of estimation the expected value in the case when a random variable has skewed probability distribution was considered e.g. by Carroll and Ruppert (1988), Chandra and Chambers (2006), Chen and Chen (1996), Karlberg (2000). Their results are based on trans-formation of skewed da ..."
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data. In the paper another approach is presented. The proposed estimators are constructed on the rather well known following property. Kendall and Stuart (1967) showed that the covariance between sample variance and sample mean is proportional to the third central mo-ment of a variable. This property
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