Variance       Article     History   Tree Map
  Encyclopedia of Keywords > Information > Evaluation > Analysis > Variance   Michael Charnine

Keywords and Sections
Review of Short Phrases and Links

    This Review contains major "Variance"- related terms, short phrases and links grouped together in the form of Encyclopedia article.


  1. Variance is the square of the standard deviation. (Web site)
  2. The variance is a measure of the overall size of the deviations from the mean. (Web site)
  3. The variance is a measure of spread or dispersion among values in a data set. (Web site)
  4. The variance is the squared differences from the average.
  5. Variance is the average of the squared deviations of each observation in the set from the arithmetic mean of all of the observations. (Web site)

Sample Variance

  1. Being a function of random variables, the sample variance is itself a random variable, and it is natural to study its distribution.
  2. A- true B- false C- no valid answer 182 2 0 ch2d 2 The sample variance. (Web site)
  3. Therefore, to prove that the sample variance is unbiased, we will show that operatorname{E}{ s^2} = sigma^2.

Variance Does

  1. The converse is not true: there are distributions for which the expected value exists, but the variance does not.
  2. It can be proven easily from the definition that the variance does not depend on the mean value μ.


  1. The normal and modified Allan variances and total variance should be identical for an averaging factor of 1. (Web site)
  2. For other averaging factors, the modified Allan variance should be approximately one-half the normal Allan variance for white FM noise and t t 0. (Web site)
  3. The Allan Deviation is a square root of Allan variance. (Web site)

Total Variance

  1. Percent of variance explained or percent of total variance is the ratio of within-group variance to total variance.
  2. This property is known as variance decomposition or the law of total variance and plays an important role in the analysis of variance. (Web site)
  3. The normal and overlapping Allan variances and total variance should be approximately equal. (Web site)


  1. Many distributions, such as the Cauchy distribution, do not have a variance because the relevant integral diverges.
  2. It is because of this analogy that such things as the variance are called moments of probability distributions.
  3. Each diagonal entry in a c j matrix is actually the amount of variance in the corresponding variable explained by that factor. (Web site)
  4. A simple bimodal distribution, in this case a mixture of two normal distributions with the same variance but different means. (Web site)
  5. Or, if you only have estimates of the error variable for each data point, it usually suffices to use those estimates in place of the true variance.

Population Variance

  1. We will demonstrate why s 2 is an unbiased estimator of the population variance.
  2. Naively computing the variance by dividing by n instead of n -1 systematically underestimates the population variance.
  3. When dealing with the complete population the (population) variance is a constant, a parameter which helps to describe the population.

Random Variable

  1. That is, if the variable is "displaced" an amount b by taking X + b, the variance of the resulting random variable is left untouched.
  2. We can also derive the mean and variance of a random variable.
  3. The Delta method uses second-order Taylor expansions to approximate the variance of a function of one or more random variables.
  4. The variance of a real-valued random variable is its second central moment, and it also happens to be its second cumulant.

Standard Deviation

  1. It can be expressed by the variance or the standard deviation.
  2. The four most common measures of variation are the range, variance, standard deviation, and coefficient of variation. (Web site)
  3. The s chart is used for pooled estimates of population standard deviation from the variance.

Squared Deviation

  1. Higher kurtosis means more of the variance is due to infrequent extreme deviations, as opposed to frequent modestly-sized deviations.
  2. The absolute deviation from the mean provides a more robust measure of the width of a distribution than the variance. (Web site)
  3. Remember that the variance is computed as the sum of squared deviations from the overall mean, divided by n-1 (sample size minus one). (Web site)


  1. Therefore the variance is 7.5 --- 6.25 = 1.25, which is indeed the same result obtained earlier with the definition formulas. (Web site)
  2. The formula for the variance presented above is a definitional formula, it defines what the variance means.


  1. This is merely a special case of the general definition of variance introduced above, but restricted to finite populations.
  2. A common method is estimating the variance of large (finite or infinite) populations from a sample.


  1. Suppose that the women have a mean length of 160 and that the variance of their lengths is 50.
  2. Then, for the total group of men and women combined, the variance of the body lengths will be 75 + 100 = 175.

Square Root

  1. An important measure of dispersion is the standard deviation, which is the square root of the variance (which is itself a measure of dispersion).
  2. A more understandable measure is the square root of the variance, called the standard deviation.
  3. The sample standard deviation is the square root of the sample variance. (Web site)

Commonly Referred

  1. The unit of variance is the square of the unit of observation.
  2. For example, the variance of a set of heights measured in centimeters will be given in square centimeters.
  3. This variance is a nonnegative-definite square matrix, commonly referred to as the covariance matrix.
  4. This variance is a positive semi-definite square matrix, commonly referred to as the covariance matrix.


  1. The variance of a finite sum of uncorrelated random variables is equal to the sum of their variances. (Web site)
  2. This is because the variance of the sum of two independent random variables is the sum of their variances.
  3. The ANOVA table decomposes the variance into the following component sum of squares: Total sum of squares. (Web site)


  1. It is the square root of the variance, and is generally written -- ( sigma).
  2. An estimate of the noise variance sigma^2. (Web site)

Analysis of Variance

  1. Multivariate analysis of variance.
  2. Stated in this manner, the discriminant function problem can be rephrased as a one-way analysis of variance (ANOVA) problem. (Web site)


  1. Multiplying by a constant: If the values of the variable are multiplied by a constant number, then the variance is multiplied by the square of the constant.
  2. One of these is that the error term has a constant variance.


  1. A loop's score is proportional to the inverse of the variance of its controller output.
  2. If a loop has a negligible PV variance, then it is given an arbitrarily high score.


  1. It would seem that the sample mean is a better estimator since, as , the variance goes to zero.
  2. When OLS is applied to heteroscedastic models the estimated variance is a biased estimator of the true variance.


  1. The formula states that the variance of a sum is equal to the sum of all elements in the covariance matrix of the components. (Web site)
  2. Show that cov X X var X . Thus, covariance subsumes variance.


  1. Phenotypic variance can be conceptually partitioned into its genetic and its environmental components in terms of a multiple regression equation.
  2. AMOVA produces estimates of variance components and F-statistic analogs (designated as phi-statistics). (Web site)
  3. Next, standardize the above variance components.


  1. To see this, imagine that "math" and "verbal" factors explain roughly equal amounts of variance in a population. (Web site)
  2. In the above case, the value <.05 in that column indicates that the variance of the two groups, clerks and managers, is not equal.


  1. In the course of statistical measurements, sample sizes so small as to warrant the use of the unbiased variance virtually never occur.
  2. The variance according to the definitions 3 or 4 is sometimes called the 'unbiased estimate'.
  3. This gives an unbiased estimate for the variance of the data with n-1 as the divisor. (Web site)


  1. Variance is analogous to the concept of moment of inertia in classical mechanics.
  2. The second moment represents the variance of the distribution.

Post Hoc

  1. This post hoc test can be used to determine the significant differences between group means in an analysis of variance setting. (Web site)
  2. Techniques from General Linear Model include single- and multifactor analysis of variance with use of linear contrasts and post hoc comparisons.

Variance Estimate

  1. Because s 2 is a variance estimate and is based on a finite sample, it too is sometimes referred to as the sample variance.
  2. The na-ve variance estimate is  EMBED Equation.3  . (Web site)


  1. By contrast, if the variable is multiplied by a scaling factor a, the variance is multiplied by a 2.
  2. See also algorithms for calculating variance.
  3. The variance of random variable X is typically designated as , , or simply -- 2. (Web site)
  4. The variance is not expressed in the same units as the observations. (Web site)
  5. Note that the n-1 in the denominator above contrasts with the equation for population variance.


  1. That is, the variance of the mean decreases with n. (Web site)
  2. Many computational formulas for the variance are based on this equality: The variance is equal to the mean of the squares minus the square of the mean. (Web site)
  3. To understand standard deviation, keep in mind that variance is the average of the squared differences between data points and the mean.
  4. Variance s 2, however, is the average squared deviations about the mean m . (Web site)


  1. Encyclopedia of Keywords > Information > Evaluation > Analysis
  2. Science > Mathematics > Statistics > Probability
  3. Information > Science > Mathematics > Statistics
  4. Encyclopedia of Keywords > Nature
  5. Encyclopedia of Keywords > Thought > Problems
  6. Books about "Variance" in

Book: Keywen Category Structure

  Short phrases about "Variance"
  Originally created: August 16, 2007.
  Links checked: January 22, 2013.
  Please send us comments and questions by this Online Form
  Please click on Move Up to move good phrases up.
0.0228 sec. a=1..