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.

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In Bayesian statistical inference, the loss function plays an important role, and symmetric loss function, such as the squared error loss L([?

A novel Bayesian algorithm for evaluation lifetime performance of exponential model

The purpose of the present study is to detect the statistical reasoning errors that academic psychologists make when presented with the results of a statistical inference test.

Interpretation of the p value: a national survey study in academic psychologists from Spain/Interpretacion del valor p: una encuesta nacional entre profesores espanoles de Psicologia

In the beginning, a brief review of the main contributors to statistical inference, first developed by Sir Ronald Fisher (1890-1962) and after improved in 1933 by Jerzy Neyman and Egon Pearson (2) (to be not confounded with the developer of the well-known Pearson product-moment correlation coefficient, Karl Pearson, who actually was Egon's father), introduces the readers from a historical point of view to what is the principal approach used in rehabilitation research, namely the Neyman-Pearson approach.

Distinguishing between statistical significance and practical/clinical meaningfulness using statistical inference

1976) make it clear how they see the place of resampling methods in relation to conventional methods of teaching statistical inference.

Building intuitions about statistical inference based on resampling

This paper highlights the role of various forms of assessments of graduate students' attitude towards statistics and conceptions on statistical inference to inform and improve instruction in this area.

Graduate students' conceptions of statistical inference

This monograph presents a philosophical treatise of various models and interpretations regarding statistical inference based on Bayesian epistemology.

John Williamson: In Defence of Objective Bayesianism

This text for first- and second-year graduate students covers theory and methods of nonparametric statistical inference procedures.

Nonparametric statistical inference, 5th ed

Chapter 9-12 discuss statistical inference, hypothesis testing and ANOVA.

Business Statistics

The APA Task Force on Statistical Inference recommended that researchers provide effect-size estimates for primary study outcomes and whenever reporting p values (Wilkinson & the Task Force on Statistical Inference, 1999).

The first word: a letter from the co-editors: Effect sizes--an explanation of JAA editorial policy

It should be required reading for all statisticians, mathematicians and scientists as it shows how religious beliefs control statistical inference.

Christian and Humanist Foundations for Statistical Inference: Religious Control of Statistical Paradigms

There is never any absolute guarantee that a statistical inference will turn out to be correct--just a likelihood.

Scrutinizing science behind the scenes

Quantitative research encompasses a breadth of methodology, including case reports, controlled experiments, quasi-experiments, statistical simulations, surveys, observational studies, and meta-analyses (Wilkinson & the Task Force on Statistical Inference, 1999).

Publishing quantitative manuscripts in Counselor Education and Supervision: general guidelines and expectations