Probability and Statistics for Engineering and the Sciences

By Eric R. Ziegel. Technometrics, 2004

1,521 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/32582d605b80036e8ceb7c6b96095c0fb7af4b23

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

In Statistics and Probability

Citations in the corpus

How useful are your comments?: analyzing and predicting youtube comments and comment ratings (2010, methodology): “We then used three separate one-way ANOVA (Analysis of Variance) procedures [6], a statistical test of whether the means of several groups are all equal, to verify the null hypothesis, H0, for each variable negativity (FN ), objectivity (FO) and positivity (FP ).”
Spatial Cluster Analysis (2008, methodology): “His disparity statistic is an adaptation of the classical test for inference of two population proportions (Devore, 2000) to the comparison of rates measured in two sub-populations, labeled as reference and target populations.”
Automatic identification of user goals in Web search (2005, background): “05 [25, 22], which indicates that the feature is effective in predicting the i(q) value.”
A discrete particle swarm optimization algorithm for the no-wait flowshop scheduling problem (2008, methodology): “To test the performance of the DPSO and DPSOVND algorithms, a series of the paired t-test at the 95% significance level was carried out [34].”
PocketLens: Toward a personal recommender system (2004, methodology): “There are several ways to formalize this idea of agreement, for example as cosine similarity, or Pearson correlation [Devore 1995].”
High-order limit state functions in the response surface method for structural reliability analysis (2008, methodology): “The test is performed by calculating values of the t-statistics [6],”
The curious case of Mercury's internal structure (2013, methodology): “…associated with C / MR 2 and C m / C are normally distributed [ Margot et al ., 2012], we can calculate p values for the hypothesis that a given individual internal structure model ’ s moment of inertia parameters are the same as the observed values using a standard z test [ Devore , 1995].”
Active Model Selection (2004, methodology): “This family is particularly convenient for representing and updating priors [Dev95].”
Assessing the impacts of parameter uncertainty for computationally expensive groundwater models (2006, methodology): “Using the results from 10 trials, a two sample t test [Devore, 2004] was performed to test the hypothesis of the equality of the mean error in estimation of the true output by ACUARS and GLUE versus the alternative that they are not equal.”
Complexity, system integration, and susceptibility to change: Biodiversity connection (2005, background): “Hence the expected number of components successfully assembled, called E, is the average of the z values weighed by their probabilities (see e.g., Devore, 2004, p. 112 ), that is”
In situ growth of Gallionella biofilms and partitioning of lanthanides and actinides between biological material and ferric oxyhydroxides (2003, methodology): “In the present case data were tested assuming that the sample was part of a population in which ρ = 0.9 (Alder & Roessler, 1977; Devore, 1999).”
Impact of radio irregularity on wireless sensor networks (2004, methodology): “Table 2 shows the likelihood values and the parameters of the Weibull distribution that fits our experimental data.”
Is mutation an appropriate tool for testing experiments? [software testing] (2005, methodology): “An equivalent, non-parametric Mann-Whitney Test [7, 22] yields the same results.”
On the film density using high power impulse magnetron sputtering (2010, neutral): “[35]).”
Anomalous system call detection (2006, methodology): “The sample correlation coef.cient r between two random variables X and Y is de.ned as [Devore 1982]: yy n asixasi - ( asix)( asi ) r(X , Y ) = (9) yy n (asix)2 - ( asix)2n (asi )2 - ( asi )2 where X = as1 x , as2 x , ... , asx is, for our purposes, the sequence of model out n puts (i.e.,…”
A comprehensive framework for verification, validation, and uncertainty quantification in scientific computing (2011, background): “Next, a prediction interval [47] is computed at the stagnation pressure where we are interested in estimating the model form uncertainty (i.”