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## Statistical Decision Theory

### Estimation and Inferential Statistics (2015-01-01): 181-235 , January 01, 2015

In this chapter we discuss the problems of point estimation, hypothesis testing and interval estimation of a parameter from a different standpoint.

## Theory of Testing of Hypothesis

### Estimation and Inferential Statistics (2015-01-01): 63-102 , January 01, 2015

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.

## Non-parametric Test

### Estimation and Inferential Statistics (2015-01-01): 145-179 , January 01, 2015

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.

## Back Matter - Estimation and Inferential Statistics

### Estimation and Inferential Statistics (2015-01-01) , January 01, 2015

## Estimation and Inferential Statistics

### Estimation and Inferential Statistics (2015-01-01) , January 01, 2015

## Methods of Estimation

### Estimation and Inferential Statistics (2015-01-01): 47-61 , January 01, 2015

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.

## Interval Estimation

### Estimation and Inferential Statistics (2015-01-01): 131-144 , January 01, 2015

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).

## Theory of Point Estimation

### Estimation and Inferential Statistics (2015-01-01): 1-45 , January 01, 2015

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).

## Likelihood Ratio Test

### Estimation and Inferential Statistics (2015-01-01): 103-129 , January 01, 2015

In the previousLikelihood Ratio Test chapter, we have seen that UMP or UMP-unbiased tests exist only for some special families of distributions, while they do not exist for other families.