statistical inference


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Related to statistical inference: Statistical hypothesis

statistical inference

[stə′tis·tə·kəl ′in·frəns]
(statistics)
The process of reaching conclusions concerning a population upon the basis of random samplings.

statistical inference

see PROBABILITY, STATISTICS.
References in periodicals archive ?
The statistical inferences of these process capability indices have drawn great attention.
What I would recommend in everyday practice, therefore, is to make statistical inference using the method that most likely would help us in understanding the size of an effect.
2011) more recently report significantly better outcomes on test items assessing statistical inference for tertiary students taught a randomisation-based curriculum (modelled on Rossman and Chance (2008)) compared to a more traditional curriculum.
The focus on the teaching of statistical inference at the graduate level is relevant as the concepts and methods of Inferential Statistics play a vital role in designing and interpreting empirical results in any scientific discipline.
The population from which the sample is drawn affects almost every conclusion in a manuscript (Wilkinson & the Task Force on Statistical Inference, 1999).
With its unequal values for clinical Type 1 and Type 2 errors, a clinical inference is superficially similar to a statistical inference based on statistical Type I and II errors.
For example, statistical fundamentals (such as the normal distribution and probability) are presented within the context of sampling theory early on in the text, which lays the groundwork for the later chapter on quantitative data analysis, which discusses issues of central tendency, dispersion, and statistical inference.
There are a number of issues involved here and we feel that an understanding of the nature of hypothesis testing and statistical inference for spatial data should be a requirement of good practice.
Scientists and researchers can now perform mass-spectrometry data analysis, perform statistical inference and prediction, view graphs, and conduct enhanced genomic and proteomic sequence analysis.
Articles in the issue include 1) "Distribution of Clinical Covariates at Detection of Cancer: Stochastic Modeling and Statistical Inference," 2) "Planning Public Health Programs and Scheduling: Breast Cancer," 3) "Planning of Randomized Trials," 4) "The Use of Modeling to Understand the Impact of Screening on U.
In small studies or in subgroup analyses with limited sample size, the fact that comorbidity scores reduce the number of variables that need to be adjusted will improve statistical inference.

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