statistical inference

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Related to statistical inference: Statistical hypothesis

Statistical inference

A statistical method of drawing conclusions on unknown properties of a population based on a random sampling of data from that population.

statistical inference

a process by which we infer conclusions about a statistical POPULATION from which only a SAMPLE has been drawn. For example, if one million Britons buy bicycles each year, and 200 are asked why they do so, 50% may say because it helps to keep them fit. From this sample one may infer that 50% of the total population of one million Britons buying bicycles do so for this reason. However, it is not possible to say with 100% accuracy that this is the case unless the views of all one million were obtained. Nevertheless, it is possible to say with reasonable confidence that the estimation of 50% is correct for the whole population.
References in periodicals archive ?
Distinguishing between statistical significance and practical/clinical meaningfulness using statistical inference.
This heterogeneity leads to Poisson over-dispersion which has to be properly accounted for to provide reliable statistical inferences.
By hypothesizing nevertheless the full availability of such knowledge, we obtain a clear separation between problems of statistical inference arising from the variability of finite samples, and problems of identification in which we explore the limits to which inference even from an infinite number of observations is suspect.
The last step gives the analyst a tool to measure the possibility of error and can provide a basis for evaluating the findings and concepts used in studies based on statistical inference.
There are, however, valuable lessons here which transcend statistical inference.
At this point I think it is worth emphasizing that the use of statistical inference to draw conclusions about the null hypothesis assumes that the underlying probability model adequately represents the distributions and variations in the real-world situation.
Following the patient's discharge from the hospital variations are entered into a data base from which statistical inference can be drawn.
In Hardigree and Anderson's discussion of the empirical information used in our study (Hoyt and Trieschmann, 1991), their recurrent theme is that the number of companies included in the study constituted an inadequate sample size for purposes of statistical inference.
In addition, the typical lack of rendom sampling in this kind of field study prohibits statistical inference from the sample to a larger population.
It provides an impressive library ranging from statistical inference functions such as t-tests to Financial Options calculations that work out of the box and at the fraction of the cost of developing from scratch or licensing other statistical packages.
SEDAL aims to develop the next generation of statistical inference methods for EO data analysis.
The book wraps up with transformation of random variables, modes of convergence, the weak law of large numbers, and the central limit theorem, with a final chapter giving an overview of statistical inference.

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