For managerial decision making, sometimes one has to carry out tests of significance.
OF VARIANCE (ANOVA)
For managerial decision making,
sometimes one has to carry out tests of significance. The analysis of variance
is an effective tool for this purpose. The objective of the analysis of
variance is to test the homogeneity of the means of different samples.
According to R.A. Fisher, “analysis
of variance is the separation of variance ascribable to one group of causes
from the variance ascribable to other groups”.
Assumptions of ANOVA
The technique of ANOVA is mainly
used for the analysis and interpretation of data obtained from experiments.
This technique is based on three important assumptions, namely
1. The parent population is normal.
2. The error component is
distributed normally with zero mean and constant variance.
3. The various effects are additive in nature.
The technique of ANOVA
essentially consists of partitioning the total variation in an experiment into
components of different sources of variation. These sources of variations are
due to controlled factors and uncontrolled factors. Since the variation in the sample
data is characterized by means of many components of variation, it can be
symbolically represented in the mathematical form called a linear model for the
Tags : Research Methodology - Analysis Of Variance
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