Hypothesis Testing

  title={Hypothesis Testing},
  author={Guy Lebanon}
We have seen so far two types of statistical estimation frameworks: confidence intervals and point estimation. Hypothesis testing is a third inference framework that is concerned with choosing a hypothesis supported by available data out of a number of competing alternatives. We start with the basic definitions and then proceed to describe a few important cases. We assume that we have data X 1 ,. .. , X n sampled from a distribution characterized by a parameter θ. A hypothesis is a set of… 

On the false discovery rates of a frequentist: Asymptotic expansions

Consider a testing problem for the null hypothesis H0 : 2 0. The standard frequentist practice is to reject the null hypothesis when the p-value is smaller than a threshold value , usually 0:05. We

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This article discusses dealing with unpaired (independent) parametric data, and a systematic approach is used to determine if the null hypothesis is valid.

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We examined theories of hypothesis testing strategy in Wason’s 2-4-6 task. Twenty-one undergraduate students were given single trials that featured a hypothesis and an example conforming to the

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A semiparametric problem of two-sample hypothesis testing for a class of latent position random graphs is considered and a notion of consistency is formulated and a valid test is proposed for the hypothesis that two finite-dimensional random dot product graphs on a common vertex set have the same generating latent positions.

A Note on Sufficient Conditions for Valid Unmodified t Testing in Correlation Analysis with Autocorrelated and Heteroscedastic Sample Data

Traditionally, sphericity (i.e., independence and homoscedasticity for raw data) is put forward as the condition to be satisfied by the variance–covariance matrix of at least one of the two

Article 6. An introduction to hypothesis testing. Parametric comparison of two groups—1

It is shown that statistical inference enables general conclusions to be drawn from specific data, for example estimating a population's mean from a sample mean, which is fundamental to most medical investigations.

Statistical Tests Based on Reliability and Precision

Abstract. The construction of a statistical test is investigated which is based only on “reliability” and “precision” as quality criteria. The reliability of a statistical test is quantified in a

Statistical and clinical significance, and how to use confidence intervals to help interpret both.

  • J. Fethney
  • Medicine
    Australian critical care : official journal of the Confederation of Australian Critical Care Nurses
  • 2010

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