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By
Sahu, Pradip Kumar; Pal, Santi Ranjan; Das, Ajit Kumar
In this chapter we discuss the problems of point estimation, hypothesis testing and interval estimation of a parameter from a different standpoint.
By
Sahu, Pradip Kumar; Pal, Santi Ranjan; Das, Ajit Kumar
Consider a random sample from an infinite or a finite Population
population. From such a sample or samples,Sample
we try to draw inference regarding population.
By
Sahu, Pradip Kumar; Pal, Santi Ranjan; Das, Ajit Kumar
In parametric testsParametric test
we generally assume a particular form of the populationPopulation
distribution (say, normal distribution)Normal distribution
from which a random sampleRandom sample
is drawn and we try to construct a test criterion (for testing hypothesis regarding parameter of the population) and the distribution of the test criterion depends upon the parent population.
more …
By
Sahu, Pradip Kumar; Pal, Santi Ranjan; Das, Ajit Kumar
In chapter one, we have discussed different optimum properties of good point estimators viz. unbiasedness, minimum variance, consistencyConsistency
and efficiencyEfficiency
which are the desirable properties of a good estimator.
By
Sahu, Pradip Kumar; Pal, Santi Ranjan; Das, Ajit Kumar
InPoint Estimation
point estimationEstimation
when a random sampleRandom sample
$$ \left( {X_{1} ,X_{2} , \ldots ,X_{n} } \right) $$
is drawn from a populationPopulation
having distribution functionDistribution function
$$ F_{\theta } $$
and
$$ \theta $$
is the unknown parameter (or the set of unknown parameter).
more …
By
Sahu, Pradip Kumar; Pal, Santi Ranjan; Das, Ajit Kumar
In carrying out any statistical investigation, we start with a suitable probability model for the phenomenon that we seek to describe (the choice of the model is dictated partly by the nature of the phenomenon and partly by the way data on the phenomenon are collected. Mathematical simplicity is also a point that is given some consideration in choosing the model).
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By
Sahu, Pradip Kumar; Pal, Santi Ranjan; Das, Ajit Kumar
1 Citations
In the previousLikelihood Ratio Test
chapter, we have seen that UMP or UMPunbiased tests exist only for some special families of distributions, while they do not exist for other families.
