Page 349 - DMTH404_STATISTICS

Richa Nandra, Lovely Professional University Unit 24: Sampling Distributions

Unit 24: Sampling Distributions Notes

CONTENTS

Objectives
Introduction
24.1 Distinction between Parameter and Statistic
24.2 Sampling Distribution of Sample Mean

24.2.1 Nature of the Sampling Distribution of Mean
24.2.2 Sampling Distribution of the Difference Between two Sample Means
24.3 Sampling Distribution of the Number of Successes
24.3.1 Sampling Distribution of Proportion of Successes

24.3.2 Sampling Distribution of the Difference of two Proportions
24.4 Summary
24.5 Keywords
24.6 Self Assessment

24.7 Review Questions
24.8 Further Readings

Objectives

After studying this unit, you will be able to:

 Distinction Between Parameter and Statistic
 Sampling Distribution of Sample Mean
 Sampling Distribution of the Number of Successes

Introduction

A theoretical probability distribution is constructed on the basis of the specification of the
conditions of a random experiment. In contrast to this, if the construction of the probability
distribution is based upon the random experiment of obtaining a sample from a population, the
resulting distribution is termed as a sampling distribution.
As we know that the main aim of obtaining a sample from a population is to draw certain
conclusions about it. The process of drawing such conclusions, known as 'Statistical Inference', is
based upon the rules or the framework provided by various sampling distributions.

It may be recalled here that simple random sampling is a procedure of obtaining a sample of
size n from a population of size N such that each combination of n units has an equal chance of
being selected as a sample. This definition also implies that every unit of the population has an
equal chance of being selected in the sample.

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