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Statistics
Simple Random Samples and Statistics
(m23496)
Author:
Paul E Pfeiffer
Keywords:
Matllab techniques
,
Population distribution
,
Population parameters
,
Random sample
,
Sample parameters
,
Sampling process
,
Statistic as estimator
Summary:
The (simple) random sample, is basic to much of classical statistics. Once formulated, we may apply probability theory to exhibit several basic ideas of statistical analysis. A population may be most any collection of individuals or entities. Associated with each member is a quantity or a feature that can be ... population parameters.
[Expand Summary]
The (simple) random sample, is basic to much of classical statistics. Once formulated, we may apply probability theory to exhibit several basic ideas of statistical analysis. A population may be most any collection of individuals or entities. Associated with each member is a quantity or a feature that can be assigned a number. The population distribution is the distribution of that quantity among the members of the population. To obtain information about the population distribution, we select “at random” a subset of the population and observe how the quantity varies over the sample. Hopefully, the distribution in the sample will give a useful approximation to the population distribution. We obtain values of such quantities as the mean and variance in the sample (which are random quantities) and use these as estimators for corresponding population parameters (which are fixed). Probability analysis provides estimates of the variation of the sample parameters about the corresponding population parameters.
[Collapse Summary]
Subject:
Mathematics and Statistics
Language:
English
Popularity:
81.35%
Revised:
20090918
Revisions:
8
Popularity is measured as percentile rank of page views/day over all time
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