Designing Quantitative Experiments 2010
DOI: 10.1007/978-3-642-11589-9_4
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Cited by 7 publications
(5 citation statements)
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“…where t 1−γ/2,λ 1 −λ 2 is the 100 (1−γ/2) percentage point of Student's t-distribution with λ 1 −λ 2 degrees of freedom (Wolberg 1967; NAG Fortran Library, Mark 23 2011). For 1 σ confidence intervals γ = 0.31731, and for λ 1 − λ 2 ≫ 1 we have t 1−γ/2,λ 1 −λ 2 ≈ 1.…”
mentioning
confidence: 99%
“…where t 1−γ/2,λ 1 −λ 2 is the 100 (1−γ/2) percentage point of Student's t-distribution with λ 1 −λ 2 degrees of freedom (Wolberg 1967; NAG Fortran Library, Mark 23 2011). For 1 σ confidence intervals γ = 0.31731, and for λ 1 − λ 2 ≫ 1 we have t 1−γ/2,λ 1 −λ 2 ≈ 1.…”
mentioning
confidence: 99%
“…Predictive analysis was a general method for predicting the accuracy of quantitative experiments. The use of predictive analysis allowed the designer of an experiment to estimate the accuracy that should be obtained from the experiment before the experimental setup was finalized [ 6 ]. Until now, there had been no in vivo or in vitro reports about the effects of curcumin on organisms exposed to PM 2.5 ; therefore, we collected limited data associated with PM 2.5 or curcumin available from online databases such as GEO and PubChem.…”
Section: Resultsmentioning
confidence: 99%
“…There are two essential stages in the K -Means method: determining the central position of each cluster and searching for members of each cluster. The K -Means approach works as follows [5], [22]:…”
Section: Jurnal Informatikamentioning
confidence: 99%
“…Predictions have similarities such as classification and estimation, but a prediction will look for a new value in the future by observing past data [4]. The use of prediction analysis allows an experiment's designer to estimate the accuracy that should be obtained from the experiment before completing the experimental setup [5].…”
Section: Introductionmentioning
confidence: 99%