Here is the synopsis of our sample research paper on Reliability In The Context Of Measurement Error. Have the paper e-mailed to you 24/7/365.
Essay / Research Paper Abstract
5 pages in length. The writer discusses reliability in the context of measurement error, as well as addresses the notion of statistical significance as it applies to the evaluation of correlation coefficients used as measures of
reliability. Bibliography lists 5 sources.
Page Count:
5 pages (~225 words per page)
File: LM1_TLCrelia.doc
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Unformatted sample text from the term paper:
statistic having its own sampling distribution essential to the process of statistical inference. It is important for the student to realize that while the form of these sampling distributions
varies, the concept underlying them is the same as that underlying the sampling distribution of that just developed. In other words, repeatedly drawing samples from the parent population, calculating
the relevant sample statistic and ultimately producing the distribution creates the sampling distribution. "Measurement error is a substantial problem for the analysis not only of latent interaction models, but
also of manifest moderator models based on multiple regression, when observed variables are treated as if each was a perfectly reliable measure" (Anonymous, 1997, p. node3.html).
Because most populations are large, it is normally very costly and impractical to investigate each member of the population to determine the value of the parameters.
As a practical alternative, the population is sampled and these sample statistics are used to draw inferences about the parameters. Care should be taken to ensure that the target
population is the same as the sampled population. Using one of the different sampling methods including simple random sampling, stratified random sampling and cluster sampling, the sampling distribution will
represent the probability distribution created by repeated sampling and by calculation of the sample statistics. This allows the calculation of the probability that the statistic falls into a range
of values, given that the parameters of the population are known. When comparing two different models, they can be considered when they are
two that simultaneously imply constraints on two groups of response configuration distributions such as the joint distribution and certain marginal distributions. For instance, models have been considered that simultaneously
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