DESIGN AND ANALYSIS OF EXPERIMENTS ON THE METHODS OF ESTIMATING VARIANCE COMPONENTS
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BACKGROUND OF THE STUDY
Variance measures the variability or difference from a mean or response. A variance value of 0 indicates that all values within a set of numbers are identical. Statisticians use variance to see how individual numbers or values relate to each other. Estimating variance components in statistics refers to the processes involved in efficiently calculating the variability within responses or values. Variance component are estimated when
- A new improved trait is discovered
- Variances or variability changes or alternate overtime due to environmental or genetic changes.
- A new trait is about to be defined or explained
A cardinal objective of many genetic surveys is the estimation of variance components associated with individual traits. Heritability, the proportion of variation in a trait that is contributed by average effects of genes, may be calculated from variance components. The heritability of a trait gives an indication of the ability of a population to respond to selection, and thus, the potential of that population to evolve (Lande & Shannon, 1996).Estimates of variance components are common in the discipline of animal breeding and production, where this information on the variance components is used in the development of selection regimes to improve economically important traits (Lynch & Walsh, 1998). A requirement for estimating variance components is knowledge of the relationship structure of the population.In a natural population, variance components are also of considerable interest for evolutionary studies (Boag, 1983) andalso for conservation purposes. In natural populations, however, information on relationships may be unreliable or unavailable. These estimates of relationships may be combined with phenotypic information gathered from the same individuals, allowing inferences to be made about variance components (Ritland, 1996; Mousseau et al., 1998).
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