Sampling & Sampling Distribution Series # 2

Sampling & Sampling Distribution

Population Parameter :

A measure of location or a measure of dispersion is called a parameter if it describes a

population. One seldom has data for entire population and hence one rarely is able to calculate population

parameters. Characteristics of the part infers Characteristics of the whole.

Standard Notation :

Sample statistics : It refers to a characteristics of a sample. It is denoted by lower case roman

letter.

Population Parameter : It refers to a characteristics of as sample. It is denoted by lower case Greek letters.

Selection Bias :

Selection bias when some part of target population is not in the sampled population.

Measurement Bias :

Measurement bias occurs when measuring instrument has a tendency to differ from the true

vale in one direction.

Sampling Error :

Sampling error result from taking one sample instead of examining the whole population.

Sampling errors are usually reported in probabilistic term. Difference between a sample statistics and

corresponding parameter is called sampling error. Fr Example Sampling Error

Non Sampling Error :

Selection bias & measurement bias refer to non-sampling errors. They are not attributed to

sample variability.

Census :

A census studies every member of a population. Census evaluation parameter of the population under

study.

Sample Survey :

A sample survey is a study of a sample. It estimates characteristics of a population, the sample came from.

Sampling Design :

Sampling design mainly decided the sample size and sampling techniques for a survey sample.

A sample design is the framework or road map that serves as the basis for the selection of a survey sample.

Sampling design affects all the important aspects of a sample survey.

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