Selected Definitions
1. By POPULATION we mean the aggregate or totality of objects or
individuals regarding which inferences are to be made in a sampling study.
2. By SAMPLE we mean a collection consisting of a part or a subset
of the objects or individuals or a population which is selected for the
express purpose of representing the population, that is, as a basis for
making inferences about or estimates of certain population facts.
3. A PARAMETER is a population fact which depends upon or is a function
of the scores for all the population units.
4. A STATISTIC is a sample fact which depends upon the scores of
the particular sampling units comprising a sample.
5. SAMPLING ERROR is simply the difference between the value of a
population parameter and that of the corresponding statistic.
6. The SAMPLING DISTRIBUTION of a statistic is the relative frequency
distribution of an infinity of determinations of the value of this statistic,
each determination being based on a separate sample of the same size and
selected independently and by the same prescribed procedure from the same
population.
7. The STANDARD ERROR of any statistic is the standard deviation
of its sampling distribution.
8. If the mean of a sampling distribution of a statistic coincides with,
or equals the corresponding population parameter, it (statistic) is said
to be unbiased. If, on the other hand, the mean of its sampling distribution
does not coincide with the parameter, it is said to be BIASED.
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