variance|variances in English
noun
['var·i·ance || 'verɪəns /'veər-]
act or instance of variation; divergence; discrepancy, strife, discord
Use "variance|variances" in a sentence
1. We use this estimate and its variance to estimate absolute density, absolute abundance, and their variances.
2. Equality (or "homogeneity") of variances, called homoscedasticity — the variance of data in groups should be the same.
3. Explanation of variances This section provides space for institutions to comment on significant variances.
4. Supplementary information on significant variances
5. The main variances resulted from:
6. Homoscedasticity (the shock variances are constant).
7. Progress report and explanation of variances :
8. Variance (Est
9. Are there any zoning variances pending?
10. Explained variance
11. with a variance
12. Progress Report and Explanations of Variances 7.
13. Calculated estimate variance
14. (c) variances between estimated aid and aid applied for.
15. VARIANCE(value; value
16. In probability theory and statistics, a Covariance matrix (also known as auto-Covariance matrix, dispersion matrix, variance matrix, or variance–Covariance matrix) is a square matrix giving the Covariance between each pair of elements of a given random vector.Any Covariance matrix is symmetric and positive semi-definite and its main diagonal contains variances (i.e., the Covariance of each
17. The traditional variance estimators and two robust variance estimators proposed by Royall and Cumberland (R.
18. A secondary cloning approach was used to partition C effects variance from genetic variance.
19. Managers are held accountable for budget variances, and are rewarded/penalized accordingly.
20. The variance of the duration
21. Consistent performance with some variance
22. The evaluation is carried out with help of analysis of variances.
23. Variances between total authorities and actual spending will be discussed later.
24. Among all the variances in agriculture, Agronomy occupies a pivotal position
25. The variance of the biased estimator was always smaller than the variance of the unbiased estimator.