Results 41 to 50 of about 3,450,267 (350)

STATISTICAL HYPOTHESIS TESTING USING FUZZY LINGUISTIC VARIABLES [PDF]

open access: yesFiabilitate şi Durabilitate, 2012
This work proposes a fuzzy statistical test of fuzzy hypotheses usinglinguistic variables. The method is based on Zadeh’s principle: the fuzzy population mean in the null hypothesis is converted to fuzzy numbers using conversion scales proposed by Chen ...
Iuliana Carmen BĂRBĂCIORU
doaj  

CONFIDENCE LEVELS AND/VS. STATISTICAL HYPOTHESIS TESTING IN STATISTICAL ANALYSIS. CASE STUDY

open access: yesScientific Papers Animal Science and Biotechnologies, 2023
Estimated parameters with confidence intervals and testing statistical assumptions used in statistical analysis to obtain conclusions on research from a sample extracted from the population.
ILEANA BRUDIU
doaj  

Quantifying the Fraction of Missing Information for Hypothesis Testing in Statistical and Genetic Studies [PDF]

open access: yes, 2008
Many practical studies rely on hypothesis testing procedures applied to data sets with missing information. An important part of the analysis is to determine the impact of the missing data on the performance of the test, and this can be done by properly ...
Kong, Augustine   +2 more
core   +3 more sources

Investigating Statistical Privacy Frameworks from the Perspective of Hypothesis Testing

open access: yesProceedings on Privacy Enhancing Technologies, 2019
Over the last decade, differential privacy (DP) has emerged as the gold standard of a rigorous and provable privacy framework. However, there are very few practical guidelines on how to apply differential privacy in practice, and a key challenge is how ...
Changchang Liu   +4 more
semanticscholar   +1 more source

Local Variation as a Statistical Hypothesis Test [PDF]

open access: yesInternational Journal of Computer Vision, 2015
The goal of image oversegmentation is to divide an image into several pieces, each of which should ideally be part of an object. One of the simplest and yet most effective oversegmentation algorithms is known as local variation (LV) (Felzenszwalb and Huttenlocher 2004). In this work, we study this algorithm and show that algorithms similar to LV can be
Peter Meer   +2 more
openaire   +4 more sources

Linking to the real world: contextual teaching and learning of statistical hypothesis testing

open access: yesLUMAT, 2021
The study used experimental research design to randomly selected senior high school students in analysing their attitude and achievement in statistics when contextual teaching is implemented.
Jeanne Marie L. Lago   +1 more
doaj   +1 more source

A statistical approach to the use of control entropy identifies differences in constraints of gait in highly trained versus untrained runners

open access: yesMathematical Biosciences and Engineering, 2011
Control entropy (CE) is a complexity analysis suitable fordynamic, non-stationary conditions which allows the inference of the control effort of a dynamical system generating the signal [4].
Rana D. Parshad   +4 more
doaj   +1 more source

Statistical significance and statistical power in hypothesis testing [PDF]

open access: yesJournal of Orthopaedic Research, 1990
AbstractExperimental design requires estimation of the sample size required to produce a meaningful conclusion. Often, experimental results are performed with sample sizes which are inappropriate to adequately support the conclusions made. In this paper, two factors which are involved in sample size estimation are detailed—namely type I (α) and type II
openaire   +3 more sources

Possibility Measure of Accepting Statistical Hypothesis

open access: yesMathematics, 2020
Taking advantage of the possibility of fuzzy test statistic falling in the rejection region, a statistical hypothesis testing approach for fuzzy data is proposed in this study.
Jung-Lin Hung   +2 more
doaj   +1 more source

A Novel Framework for Learning Automata: A Statistical Hypothesis Testing Approach

open access: yesIEEE Access, 2019
Learning automaton (LA), a powerful tool in reinforcement learning, is of crucial importance for its adaptivity in the stochastic environment and its applicability in various engineering fields.
Chong Di   +3 more
doaj   +1 more source

Home - About - Disclaimer - Privacy