scholarly journals Performance Improvement of Basketball Athletes based on Statistical Analysis

2019 ◽  
Author(s):  
Lukmannul Haqim Lubay
Keyword(s):  
Statistical Analysis ◽  
Performance Improvement

Abrasive Wear: Design of Experiment (DOE) for Determining the Wear on Crowns Used by Drilling Companies for Mineral Surveys

2013 ◽  
Vol 660 ◽  
pp. 69-74
Author(s):  
Zirlene Alves da Silva Santos ◽  
Jefferson Januário Mendes ◽  
Adilson Rodrigues da Costa
Keyword(s):  
Statistical Analysis ◽  
Chemical Composition ◽  
Abrasive Wear ◽  
Performance Improvement ◽  
Design Of Experiment ◽  
Planning Process ◽  
Field Research ◽  
Wear Test ◽  
Material Loss ◽  
Controllable Factors

Currently companies seek performance improvement for equipment and components, and an important factor that influences performance is wear. The objective of this study was to demonstrate the applicability of a methodology that was developed using literature, field research, brainstorming, optical microscopy, statistical analysis.Wear tests for drilling crown samplesfor the production process were performed. - The crown’s chemical composition was analyzed to see if it was appropriate for the soil’s mineral lithology. Having done this, a statistical analysis was made. using Minitab 16 software, specifically applying DOE (2Kfactorial) technique. With the statistical result, a prototype was produced and subjected to a wear test for analysis of material loss compared to crowns having a better performance.Thus, the conclusion reached was that the planning process improves withthis experimental probing, which helps to identify and correct controllable factors.

scholarly journals Poor numerical performance of guppies tested in a Skinner box

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Elia Gatto ◽  
Alberto Testolin ◽  
Angelo Bisazza ◽  
Marco Zorzi ◽  
Tyrone Lucon-Xiccato
Keyword(s):  
Statistical Analysis ◽  
Cognitive Load ◽  
Performance Improvement ◽  
Discrimination Task ◽  
Numerical Competence ◽  
Numerosity Discrimination ◽  
Average Accuracy ◽  
Naturalistic Setting ◽  
Numerical Performance ◽  
Skinner Box

Abstract We tested the hypothesis that part of the gap in numerical competence between fish and warm-blooded vertebrates might be related to the more efficient procedures (e.g. automated conditioning chambers) used to investigate the former and could be filled by adopting an adapted version of the Skinner box in fish. We trained guppies in a visual numerosity discrimination task, featuring two difficulty levels (3 vs. 5 and 3 vs. 4) and three conditions of congruency between numerical and non-numerical cues. Unexpectedly, guppies trained with the automated device showed a much worse performance compared to previous investigations employing more “ecological” procedures. Statistical analysis indicated that the guppies overall chose the correct stimulus more often than chance; however, their average accuracy did not exceed 60% correct responses. Learning measured as performance improvement over training was significant only for the stimuli with larger numerical difference. Additionally, the target numerosity was selected more often than chance level only for the set of stimuli in which area and number were fully congruent. Re-analysis of prior studies indicate that the gap between training with the Skinner box and with a naturalistic setting was present only for numerical discriminations, but not for colour and shape discriminations. We suggest that applying automated conditioning chambers to fish might increase cognitive load and therefore interfere with achievement of numerosity discriminations.

Statistical analysis of classification

1966 ◽  
Vol 24 ◽  
pp. 188-189
Author(s):  
T. J. Deeming
Keyword(s):  
Multivariate Analysis ◽  
Statistical Analysis ◽  
Classification Scheme ◽  
Analytical Procedure ◽  
Narrow Band ◽  
Scientific Research ◽  
Maximum Amount ◽  
Amount Of Information

If we make a set of measurements, such as narrow-band or multicolour photo-electric measurements, which are designed to improve a scheme of classification, and in particular if they are designed to extend the number of dimensions of classification, i.e. the number of classification parameters, then some important problems of analytical procedure arise. First, it is important not to reproduce the errors of the classification scheme which we are trying to improve. Second, when trying to extend the number of dimensions of classification we have little or nothing with which to test the validity of the new parameters.Problems similar to these have occurred in other areas of scientific research (notably psychology and education) and the branch of Statistics called Multivariate Analysis has been developed to deal with them. The techniques of this subject are largely unknown to astronomers, but, if carefully applied, they should at the very least ensure that the astronomer gets the maximum amount of information out of his data and does not waste his time looking for information which is not there. More optimistically, these techniques are potentially capable of indicating the number of classification parameters necessary and giving specific formulas for computing them, as well as pinpointing those particular measurements which are most crucial for determining the classification parameters.

Quantitative parallel EELS spectrum imaging developed as a new tool in AEM

1992 ◽  
Vol 50 (2) ◽  
pp. 1202-1203
Author(s):  
Gianluigi Botton ◽  
Gilles L'espérance
Keyword(s):  
Statistical Analysis ◽  
Spatial Resolution ◽  
Personal Computer ◽  
Systematic Study ◽  
Present Author ◽  
Chemical Elements ◽  
Detection Limits ◽  
Research Groups ◽  
Quantitative Performance ◽  
Spectrum Imaging

As interest for parallel EELS spectrum imaging grows in laboratories equipped with commercial spectrometers, different approaches were used in recent years by a few research groups in the development of the technique of spectrum imaging as reported in the literature. Either by controlling, with a personal computer both the microsope and the spectrometer or using more powerful workstations interfaced to conventional multichannel analysers with commercially available programs to control the microscope and the spectrometer, spectrum images can now be obtained. Work on the limits of the technique, in terms of the quantitative performance was reported, however, by the present author where a systematic study of artifacts detection limits, statistical errors as a function of desired spatial resolution and range of chemical elements to be studied in a map was carried out The aim of the present paper is to show an application of quantitative parallel EELS spectrum imaging where statistical analysis is performed at each pixel and interpretation is carried out using criteria established from the statistical analysis and variations in composition are analyzed with the help of information retreived from t/γ maps so that artifacts are avoided.

Intraindividual Variability in Development Within and Between Individuals

2001 ◽  
Vol 6 (3) ◽  
pp. 187-193 ◽  
Author(s):  
John R. Nesselroade
Keyword(s):  
Statistical Analysis ◽  
Research Design ◽  
Intraindividual Variability ◽  
Factor Analytic

A focus on the study of development and other kinds of changes in the whole individual has been one of the hallmarks of research by Magnusson and his colleagues. A number of different approaches emphasize this individual focus in their respective ways. This presentation focuses on intraindividual variability stemming from Cattell's P-technique factor analytic proposals, making several refinements to make it more tractable from a research design standpoint and more appropriate from a statistical analysis perspective. The associated methods make it possible to study intraindividual variability both within and between individuals. An empirical example is used to illustrate the procedure.

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