Sampling & Sampling Distribution series # 1

 SAMPLING AND SAMPLING DISTRIBUTIONS

Introduction

Sampling is pre-requisite of statistical inference. Sample data is used to find value of the sample

 statistics which is used to estimate corresponding unknown population parameter. Sampling is

 basically of two types namely probability sampling and non probability sampling. sampling design

 comprises two things namely sampling technique and size of the sample.

Basic Terms

population: 

The population is the entire group of individuala or objects under consideration.

Target population :

  The complete collection of observstions we want to study is called target

 population.

Sampled population : 

The population from which the sample is taken is called sampled population.

Element :

An element is a single member of a population.

Sample :

Sample is a portion chosen from the population. The sample is a part or subset of population.

 Information is obtained only from the cases included in the sample. A subset of the total number of

 measurements is called sample.

Subject :

Subject is single member of sample.

Sampling :

Good of statistical  inference is to determine something about a population based on information from sample.

 In statistical inference, samples are used to estimate some characteristics of population  i,e. parameter.

Sampling is pre-requisite of statistical inference. Sampling deals with techniques of selecting sample from

 population subject to conditions.

Smapling with Replacement :

If a population element can be selected more than one time, sampling is with replacement.

Sampling without Replacement :

If a population element can be selected only one time, sampling is without replacement.

Sampling frame :

Sampling frame is a physical list of all the elements in the population from which the sample is drawn.

Sample Statistics :

A sample counter part of corresponding population characteristics is called statistics. An estimate of a

 population para meter is called parameter is called a statistics. A measure of a location or a measure of a

 dispersion is called a statistic if it describes a sample.

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