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Prostate Cancer in the MENA Region: Attributable Burden of Behavioral and Environmental Exposures. [PDF]
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Single‐Factor Analysis in Population Dynamics
Ecology, 1959In the study of natural populations it is desirable btit not always feasible to measure the effects of all mortality factors. This requires frequent population sampling, supported by data on natural enemies, climate, and other factors, and leads to the compilation of detailed life tables for successive generations.
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Single-Factor Repeated-Measures Designs: Analysis and Interpretation
Journal of the American Academy of Child & Adolescent Psychiatry, 2002In this column we discussed the selection and interpretation of appropriate statistical tests for single-factor within-subjects/ repeated-measures designs and provided an example from the literature. The parametric tests that we discussed were the t test for paired or correlated samples and the single-factor repeated-measures ANOVA.
Jeffrey A, Gliner +2 more
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Single Factor Analysis of Variance (ANOVA)
2021This swirl lesson introduces students to theoretical and practical concepts about single-factor ANOVA analysis and an approach to conduct this type of analysis using R.
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THE ANALYSIS OF SINGLE‐FACTOR SEGREGATIONS
Annals of Eugenics, 1937The articles published by the Annals of Eugenics (1925–1954) have been made available online as an historical archive intended for scholarly use. The work of eugenicists was often pervaded by prejudice against racial, ethnic and disabled groups. The online publication of this material for scholarly research purposes is not an endorsement of those views
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Single Factor Analysis of Variance
1986The basic principles of analysis of variance were developed by R.A. Fisher (later Sir Ronald Fisher), who is regarded by many as the greatest figure in the history of statistics. Fisher was possessed of amazing industry: he wrote seven very influential books and almost three hundred articles.
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Single factor analysis in MML mixture modelling
1998Mixture modelling concerns the unsupervised discovery of clusters within data. Most current clustering algorithms assume that variables within classes are uncorrelated. We present a method for producing and evaluating models which account for inter-attribute correlation within classes with a single Gaussian linear factor.
Russell T. Edwards, David L. Dowe
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Single Factor Analysis in Grading Jobs
2017Although human resources management is important in organization, its tenet of job evaluation is significant. Job evaluation is a management approach that enables employers to grade and reward jobs in comparison to what they are worth in the company in an equitable manner.
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