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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