probability Gamification of Statistics and Probability Education: A Mobile Courseware Approach By Published On :: 2023-08-04 Aim/Purpose: The study examined how the developed mobile courseware can be used as instructional material to improve senior high school statistics and probability learning, particularly during distance learning caused by the COVID-19 pandemic. The study also aims to assess the gamified mobile courseware’s engagement, functionality, aesthetics, and information quality using the Mobile App Rating Scale (MARS) and a researcher-made Gamified Mobile Courseware Assessment Tool (GMCET). Background: The need to investigate the effectiveness of incorporating game-based elements into mathematics courses through innovative instructional materials inspired the study. The COVID-19 pandemic has made distance learning a necessity, and gamified mobile courseware is a potential solution to improve learning outcomes and engagement in mathematics courses. Methodology: The study employed a descriptive-evaluative method with quantitative and qualitative data to achieve its objectives. Five IT practitioners assessed the developed courseware using the MARS regarding engagement, functionality, aesthetics, and information. A researcher-made GMCET was also used to evaluate the app’s content quality, learning objectives, content presentation, learning assessment, and usability. Five math experts and 12 math teachers rated the app using the GMCET. The study used weighted mean to analyze the quantitative data and content analysis for the qualitative data. Contribution: The study provides insights into the strengths and weaknesses of gamified mobile courseware from the perspective of IT practitioners, math experts, and math teachers. The study’s findings can inform improvements in future iterations of courseware, and the study provides a valuable guide for practitioners looking to develop gamified mobile courseware for mathematics courses. Findings: The quantitative results based on the weighted mean indicate that the IT practitioners had a moderately positive perception of the developed courseware across all categories. At the same time, the math teachers and math experts showed highly positive perceptions of the gamified mobile courseware in Statistics and Probability, rating it highly across all categories. The qualitative data analysis through content analysis highlights the need for improving the user interface, usability, user experience design, user control, flexibility in interaction, data quality, reliability, and user privacy of the developed app. Recommendations for Practitioners: Practitioners can use the study’s findings to improve the design of gamified mobile courseware for mathematics courses and other content areas. The study recommends that practitioners focus on improving the user interface, usability, user experience design, user control, flexibility in interaction, data quality, reliability, and user privacy of gamified mobile courseware. Recommendation for Researchers: Future research can build on this study’s findings by exploring the use of gamified mobile courseware in other mathematical courses and other subject areas. Further research can also examine how gamified mobile courseware can improve learning outcomes for students with different learning needs. Impact on Society: The study’s findings could improve the effectiveness of gamified mobile courseware in enhancing student learning outcomes in mathematics courses. This can lead to better student performance, improved engagement, and increased interest in mathematics courses, positively impacting society. Future Research: Future research can explore using gamified mobile courseware in other mathematics courses and other subject areas. Additionally, future studies can examine how gamified mobile courseware can improve learning outcomes for students with different learning needs. Further research can also investigate the impact of gamified mobile courseware on student motivation, interest, and performance in mathematics courses. Full Article
probability Chance, Probability and Atheists By www.salaf.com Published On :: Fri, 26 Apr 2019 07:56:41 GMT Full Article
probability A note on the Hendrickson–Lattman phase probability distribution and its equivalence to the generalized von Mises distribution By journals.iucr.org Published On :: 2024-02-16 Hendrickson & Lattman [Acta Cryst. (1970), B26, 136–143] introduced a method for representing crystallographic phase probabilities defined on the unit circle. Their approach could model the bimodal phase probability distributions that can result from experimental phase determination procedures. It also provided simple and highly effective means to combine independent sources of phase information. The present work discusses the equivalence of the Hendrickson–Lattman distribution and the generalized von Mises distribution of order two, which has been studied in the statistical literature. Recognizing this connection allows the Hendrickson–Lattman distribution to be expressed in an alternative form which is easier to interpret, as it involves the location and concentration parameters of the component von Mises distributions. It also allows clarification of the conditions for bimodality and access to a simplified analytical method for evaluating the trigonometric moments of the distribution, the first of which is required for computing the best Fourier synthesis in the presence of phase, but not amplitude, uncertainty. Full Article text
probability A 10% swing in win probability corresponds (approximately) to a 0.4% swing in predicted vote By statmodeling.stat.columbia.edu Published On :: Sat, 02 Nov 2024 20:46:56 +0000 There’s some confusion regarding jumps in election forecasts. New information is coming in every day, so it makes sense that forecasts change too. But they don’t change very much. Each new piece of information tells you only a little bit. … Continue reading → Full Article Bayesian Statistics Political Science
probability The singularity probability of a random symmetric matrix is exponentially small By www.ams.org Published On :: Wed, 16 Oct 2024 14:24 EDT Marcelo Campos, Matthew Jenssen, Marcus Michelen and Julian Sahasrabudhe J. Amer. Math. Soc. 38 (), 179-224. Abstract, references and article information Full Article
probability On the discrepancy of low-dimensional probability measures By www.ams.org Published On :: Tue, 05 Nov 2024 14:10 EST Christian Weiss Theor. Probability and Math. Statist. 111 (), 199-209. Abstract, references and article information Full Article
probability Probability of operating an alarm clock Rubix cube, doable with hours of concentration Qauntum physicists have yet to unravel the mysteries By cheezburger.com Published On :: Tue, 22 Jun 2010 22:35:14 -0700 Probability of operating an alarm clock Full Article
probability Insight into the probability of ethoxy(pentafluoro)cyclotriphosphazene (PFPN) as the functional electrolyte additive in lithium–sulfur batteries By pubs.rsc.org Published On :: RSC Adv., 2024, 14,12754-12761DOI: 10.1039/D3RA08379A, Paper Open Access   This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.Ning Li, Yu Zhang, Shun Zhang, Lu Shi, Jie-Yu Zhang, Ke-Meng Song, Jin-Chun Li, Fang-Lei ZengEnhancing the flame retardancy of electrolytes and the stability of lithium anodes is of great significance to improve the safety performance of lithium–sulfur (Li–S) batteries.The content of this RSS Feed (c) The Royal Society of Chemistry Full Article
probability Probability of death by NCDs high in India: WHO By www.thehindu.com Published On :: Tue, 20 Jan 2015 16:17:56 +0530 Full Article Health
probability Household Portfolio Underdiversification and Probability Weighting: Evidence from the Field [electronic journal]. By encore.st-andrews.ac.uk Published On :: National Bureau of Economic Research Full Article
probability Games, gambling, and probability [electronic resource] : an introduction to mathematics / David G. Taylor, Roanoke College, Salem, VA By darius.uleth.ca Published On :: Boca Raton : Chapman & Hall/CRC Press, 2021 Full Article
probability Probability, choice, and reason [electronic resource] / Leighton Vaughan Williams. By darius.uleth.ca Published On :: Boca Raton, FL : CRC Press, 2022. Full Article
probability Probability and partial differential equations in modern applied mathematics [electronic resource] / Edward C. Waymire, Jinqiao Duan, editors By darius.uleth.ca Published On :: New York : Springer, [2005] Full Article
probability Probability theory with applications [electronic resource] / by M.M. Rao, R.J. Swift By darius.uleth.ca Published On :: New York : Springer, ©2006 Full Article
probability William Hill bids for mobile gambling provider Probability By www.eversheds.com Published On :: 2011-10-05 What? William Hill has entered into preliminary talks about a purchase of Probability, the mobile gambling company. So what? An acquisition of Probability would add to William Hill’s offering for users of smartphones and tablet computers. Pr... Full Article
probability Probability for fraud is high for quick service restaurants, Sift data shows By feedproxy.google.com Published On :: Fri, 11 Oct 2019 10:19:00 +0200 (The Paypers) Consumer expectations for convenience have increased significantly across a variety of markets, and quick-service restaurants (QSRs) are no... Full Article
probability Probability of rapid increase in trans-Arctic shipping routes is confirmed By ec.europa.eu Published On :: Thu, 16 May 2013 12:12:15 +0100 New research on climate-driven reductions in Arctic sea ice has predicted that, by 2040 to 2059, new shipping routes will become passable across the Arctic, linking the Atlantic and Pacific oceans. An increase in traffic has implications for the ecosystems of this fragile area. Full Article
probability Probability of rapid increase in trans-Arctic shipping routes is confirmed By ec.europa.eu Published On :: Thu, 16 May 2013 12:12:58 +0100 New research on climate-driven reductions in Arctic sea ice has predicted that, by 2040 to 2059, new shipping routes will become passable across the Arctic, linking the Atlantic and Pacific oceans. An increase in traffic has implications for the ecosystems of this fragile area. Full Article
probability Simulation of Integro-Differential Equation and Application in Estimation of Ruin Probability with Mixed Fractional Brownian Motion. (arXiv:1709.03418v6 [math.PR] UPDATED) By arxiv.org Published On :: In this paper, we are concerned with the numerical solution of one type integro-differential equation by a probability method based on the fundamental martingale of mixed Gaussian processes. As an application, we will try to simulate the estimation of ruin probability with an unknown parameter driven not by the classical L'evy process but by the mixed fractional Brownian motion. Full Article
probability Ensuring Fairness under Prior Probability Shifts. (arXiv:2005.03474v1 [cs.LG]) By arxiv.org Published On :: In this paper, we study the problem of fair classification in the presence of prior probability shifts, where the training set distribution differs from the test set. This phenomenon can be observed in the yearly records of several real-world datasets, such as recidivism records and medical expenditure surveys. If unaccounted for, such shifts can cause the predictions of a classifier to become unfair towards specific population subgroups. While the fairness notion called Proportional Equality (PE) accounts for such shifts, a procedure to ensure PE-fairness was unknown. In this work, we propose a method, called CAPE, which provides a comprehensive solution to the aforementioned problem. CAPE makes novel use of prevalence estimation techniques, sampling and an ensemble of classifiers to ensure fair predictions under prior probability shifts. We introduce a metric, called prevalence difference (PD), which CAPE attempts to minimize in order to ensure PE-fairness. We theoretically establish that this metric exhibits several desirable properties. We evaluate the efficacy of CAPE via a thorough empirical evaluation on synthetic datasets. We also compare the performance of CAPE with several popular fair classifiers on real-world datasets like COMPAS (criminal risk assessment) and MEPS (medical expenditure panel survey). The results indicate that CAPE ensures PE-fair predictions, while performing well on other performance metrics. Full Article
probability Distributed Stabilization by Probability Control for Deterministic-Stochastic Large Scale Systems : Dissipativity Approach. (arXiv:2005.03193v1 [eess.SY]) By arxiv.org Published On :: By using dissipativity approach, we establish the stability condition for the feedback connection of a deterministic dynamical system $Sigma$ and a stochastic memoryless map $Psi$. After that, we extend the result to the class of large scale systems in which: $Sigma$ consists of many sub-systems; and $Psi$ consists of many "stochastic actuators" and "probability controllers" that control the actuator's output events. We will demonstrate the proposed approach by showing the design procedures to globally stabilize the manufacturing systems while locally balance the stock levels in any production process. Full Article
probability Fault Tree Analysis: Identifying Maximum Probability Minimal Cut Sets with MaxSAT. (arXiv:2005.03003v1 [cs.AI]) By arxiv.org Published On :: In this paper, we present a novel MaxSAT-based technique to compute Maximum Probability Minimal Cut Sets (MPMCSs) in fault trees. We model the MPMCS problem as a Weighted Partial MaxSAT problem and solve it using a parallel SAT-solving architecture. The results obtained with our open source tool indicate that the approach is effective and efficient. Full Article
probability Method and apparatus for selectively indicating win probability By www.freepatentsonline.com Published On :: Tue, 05 May 2015 08:00:00 EDT Each play of a base game increases the likelihood of winning a bonus award. A display provides a graphical indication of the change in likelihood of winning the bonus award. In one aspect, the bonus award comprises the opportunity to play a secondary game. Full Article
probability Squirrels and Stock Brokers, Or: Innovation Dilemmas, Robustness and Probability By decisions-and-info-gaps.blogspot.com Published On :: Sun, 09 Oct 2011 11:51:00 +0000 Decisions are made in order to achieve desirable outcomes. An innovation dilemma arises when a seemingly more attractive option is also more uncertain than other options. In this essay we explore the relation between the innovation dilemma and the robustness of a decision, and the relation between robustness and probability. A decision is robust to uncertainty if it achieves required outcomes despite adverse surprises. A robust decision may differ from the seemingly best option. Furthermore, robust decisions are not based on knowledge of probabilities, but can still be the most likely to succeed.Squirrels, Stock-Brokers and Their DilemmasDecision problems.Imagine a squirrel nibbling acorns under an oak tree. They're pretty good acorns, though a bit dry. The good ones have already been taken. Over in the distance is a large stand of fine oaks. The acorns there are probably better. But then, other squirrels can also see those trees, and predators can too. The squirrel doesn't need to get fat, but a critical caloric intake is necessary before moving on to other activities. How long should the squirrel forage at this patch before moving to the more promising patch, if at all?Imagine a hedge fund manager investing in South African diamonds, Australian Uranium, Norwegian Kroners and Singapore semi-conductors. The returns have been steady and good, but not very exciting. A new hi-tech start-up venture has just turned up. It looks promising, has solid backing, and could be very interesting. The manager doesn't need to earn boundless returns, but it is necessary to earn at least a tad more than the competition (who are also prowling around). How long should the manager hold the current portfolio before changing at least some of its components?These are decision problems, and like many other examples, they share three traits: critical needs must be met; the current situation may or may not be adequate; other alternatives look much better but are much more uncertain. To change, or not to change? What strategy to use in making a decision? What choice is the best bet? Betting is a surprising concept, as we have seen before; can we bet without knowing probabilities?Solution strategies.The decision is easy in either of two extreme situations, and their analysis will reveal general conclusions.One extreme is that the status quo is clearly insufficient. For the squirrel this means that these crinkled rotten acorns won't fill anybody's belly even if one nibbled here all day long. Survival requires trying the other patch regardless of the fact that there may be many other squirrels already there and predators just waiting to swoop down. Similarly, for the hedge fund manager, if other funds are making fantastic profits, then something has to change or the competition will attract all the business.The other extreme is that the status quo is just fine, thank you. For the squirrel, just a little more nibbling and these acorns will get us through the night, so why run over to unfamiliar oak trees? For the hedge fund manager, profits are better than those of any credible competitor, so uncertain change is not called for.From these two extremes we draw an important general conclusion: the right answer depends on what you need. To change, or not to change, depends on what is critical for survival. There is no universal answer, like, "Always try to improve" or "If it's working, don't fix it". This is a very general property of decisions under uncertainty, and we will call it preference reversal. The agent's preference between alternatives depends on what the agent needs in order to "survive".The decision strategy that we have described is attuned to the needs of the agent. The strategy attempts to satisfy the agent's critical requirements. If the status quo would reliably do that, then stay put; if not, then move. Following the work of Nobel Laureate Herbert Simon, we will call this a satisficing decision strategy: one which satisfies a critical requirement."Prediction is always difficult, especially of the future." - Robert Storm PetersenNow let's consider a different decision strategy that squirrels and hedge fund managers might be tempted to use. The agent has obtained information about the two alternatives by signals from the environment. (The squirrel sees grand verdant oaks in the distance, the fund manager hears of a new start up.) Given this information, a prediction can be made (though the squirrel may make this prediction based on instincts and without being aware of making it). Given the best available information, the agent predicts which alternative would yield the better outcome. Using this prediction, the decision strategy is to choose the alternative whose predicted outcome is best. We will call this decision strategy best-model optimization. Note that this decision strategy yields a single universal answer to the question facing the agent. This strategy uses the best information to find the choice that - if that information is correct - will yield the best outcome. Best-model optimization (usually) gives a single "best" decision, unlike the satisficing strategy that returns different answers depending on the agent's needs.There is an attractive logic - and even perhaps a moral imperative - to use the best information to make the best choice. One should always try to do one's best. But the catch in the argument for best-model optimization is that the best information may actually be grievously wrong. Those fine oak trees might be swarming with insects who've devoured the acorns. Best-model optimization ignores the agent's central dilemma: stay with the relatively well known but modest alternative, or go for the more promising but more uncertain alternative."Tsk, tsk, tsk" says our hedge fund manager. "My information already accounts for the uncertainty. I have used a probabilistic asset pricing model to predict the likelihood that my profits will beat the competition for each of the two alternatives."Probabilistic asset pricing models are good to have. And the squirrel similarly has evolved instincts that reflect likelihoods. But a best-probabilistic-model optimization is simply one type of best-model optimization, and is subject to the same vulnerability to error. The world is full of surprises. The probability functions that are used are quite likely wrong, especially in predicting the rare events that the manager is most concerned to avoid.Robustness and ProbabilityNow we come to the truly amazing part of the story. The satisficing strategy does not use any probabilistic information. Nonetheless, in many situations, the satisficing strategy is actually a better bet (or at least not a worse bet), probabilistically speaking, than any other strategy, including best-probabilistic-model optimization. We have no probabilistic information in these situations, but we can still maximize the probability of success (though we won't know the value of this maximum).When the satisficing decision strategy is the best bet, this is, in part, because it is more robust to uncertainty than another other strategy. A decision is robust to uncertainty if it achieves required outcomes even if adverse surprises occur. In many important situations (though not invariably), more robustness to uncertainty is equivalent to being more likely to succeed or survive. When this is true we say that robustness is a proxy for probability.A thorough analysis of the proxy property is rather technical. However, we can understand the gist of the idea by considering a simple special case.Let's continue with the squirrel and hedge fund examples. Suppose we are completely confident about the future value (in calories or dollars) of not making any change (staying put). In contrast, the future value of moving is apparently better though uncertain. If staying put would satisfy our critical requirement, then we are absolutely certain of survival if we do not change. Staying put is completely robust to surprises so the probability of success equals 1 if we stay put, regardless of what happens with the other option. Likewise, if staying put would not satisfy our critical requirement, then we are absolutely certain of failure if we do not change; the probability of success equals 0 if we stay, and moving cannot be worse. Regardless of what probability distribution describes future outcomes if we move, we can always choose the option whose likelihood of success is greater (or at least not worse). This is because staying put is either sure to succeed or sure to fail, and we know which.This argument can be extended to the more realistic case where the outcome of staying put is uncertain and the outcome of moving, while seemingly better than staying, is much more uncertain. The agent can know which option is more robust to uncertainty, without having to know probability distributions. This implies, in many situations, that the agent can choose the option that is a better bet for survival.Wrapping UpThe skillful decision maker not only knows a lot, but is also able to deal with conflicting information. We have discussed the innovation dilemma: When choosing between two alternatives, the seemingly better one is also more uncertain.Animals, people, organizations and societies have developed mechanisms for dealing with the innovation dilemma. The response hinges on tuning the decision to the agent's needs, and robustifying the choice against uncertainty. This choice may or may not coincide with the putative best choice. But what seems best depends on the available - though uncertain - information.The commendable tendency to do one's best - and to demand the same of others - can lead to putatively optimal decisions that may be more vulnerable to surprise than other decisions that would have been satisfactory. In contrast, the strategy of robustly satisfying critical needs can be a better bet for survival. Consider the design of critical infrastructure: flood protection, nuclear power, communication networks, and so on. The design of such systems is based on vast knowledge and understanding, but also confronts bewildering uncertainties and endless surprises. We must continue to improve our knowledge and understanding, while also improving our ability to manage the uncertainties resulting from the expanding horizon of our efforts. We must identify the critical goals and seek responses that are immune to surprise. Full Article betting innovation dilemma probability proxy property robustness
probability A new orchard, and garden: or, the best way for planting, grafting, and to make any ground good, for a rich orchard: : particularly in the north and generally for the whole common-wealth as in nature, reason, situation, and all probability, may and doth a By feedproxy.google.com Published On :: London : printed by W. Wilson, for E. Brewster, and George Sawbridge, at the Bible on Ludgate-Hill, neere Fleet-bridge, 1653. Full Article
probability Branching random walks with uncountably many extinction probability vectors By projecteuclid.org Published On :: Mon, 04 May 2020 04:00 EDT Daniela Bertacchi, Fabio Zucca. Source: Brazilian Journal of Probability and Statistics, Volume 34, Number 2, 426--438.Abstract: Given a branching random walk on a set $X$, we study its extinction probability vectors $mathbf{q}(cdot,A)$. Their components are the probability that the process goes extinct in a fixed $Asubseteq X$, when starting from a vertex $xin X$. The set of extinction probability vectors (obtained letting $A$ vary among all subsets of $X$) is a subset of the set of the fixed points of the generating function of the branching random walk. In particular here we are interested in the cardinality of the set of extinction probability vectors. We prove results which allow to understand whether the probability of extinction in a set $A$ is different from the one of extinction in another set $B$. In many cases there are only two possible extinction probability vectors and so far, in more complicated examples, only a finite number of distinct extinction probability vectors had been explicitly found. Whether a branching random walk could have an infinite number of distinct extinction probability vectors was not known. We apply our results to construct examples of branching random walks with uncountably many distinct extinction probability vectors. Full Article
probability On the probability distribution of the local times of diagonally operator-self-similar Gaussian fields with stationary increments By projecteuclid.org Published On :: Fri, 31 Jan 2020 04:06 EST Kamran Kalbasi, Thomas Mountford. Source: Bernoulli, Volume 26, Number 2, 1504--1534.Abstract: In this paper, we study the local times of vector-valued Gaussian fields that are ‘diagonally operator-self-similar’ and whose increments are stationary. Denoting the local time of such a Gaussian field around the spatial origin and over the temporal unit hypercube by $Z$, we show that there exists $lambdain(0,1)$ such that under some quite weak conditions, $lim_{n ightarrow+infty}frac{sqrt[n]{mathbb{E}(Z^{n})}}{n^{lambda}}$ and $lim_{x ightarrow+infty}frac{-logmathbb{P}(Z>x)}{x^{frac{1}{lambda}}}$ both exist and are strictly positive (possibly $+infty$). Moreover, we show that if the underlying Gaussian field is ‘strongly locally nondeterministic’, the above limits will be finite as well. These results are then applied to establish similar statements for the intersection local times of diagonally operator-self-similar Gaussian fields with stationary increments. Full Article
probability Characterization of probability distribution convergence in Wasserstein distance by $L^{p}$-quantization error function By projecteuclid.org Published On :: Fri, 31 Jan 2020 04:06 EST Yating Liu, Gilles Pagès. Source: Bernoulli, Volume 26, Number 2, 1171--1204.Abstract: We establish conditions to characterize probability measures by their $L^{p}$-quantization error functions in both $mathbb{R}^{d}$ and Hilbert settings. This characterization is two-fold: static (identity of two distributions) and dynamic (convergence for the $L^{p}$-Wasserstein distance). We first propose a criterion on the quantization level $N$, valid for any norm on $mathbb{R}^{d}$ and any order $p$ based on a geometrical approach involving the Voronoï diagram. Then, we prove that in the $L^{2}$-case on a (separable) Hilbert space, the condition on the level $N$ can be reduced to $N=2$, which is optimal. More quantization based characterization cases in dimension 1 and a discussion of the completeness of a distance defined by the quantization error function can be found at the end of this paper. Full Article
probability Probability Based Independence Sampler for Bayesian Quantitative Learning in Graphical Log-Linear Marginal Models By projecteuclid.org Published On :: Tue, 11 Jun 2019 04:00 EDT Ioannis Ntzoufras, Claudia Tarantola, Monia Lupparelli. Source: Bayesian Analysis, Volume 14, Number 3, 797--823.Abstract: We introduce a novel Bayesian approach for quantitative learning for graphical log-linear marginal models. These models belong to curved exponential families that are difficult to handle from a Bayesian perspective. The likelihood cannot be analytically expressed as a function of the marginal log-linear interactions, but only in terms of cell counts or probabilities. Posterior distributions cannot be directly obtained, and Markov Chain Monte Carlo (MCMC) methods are needed. Finally, a well-defined model requires parameter values that lead to compatible marginal probabilities. Hence, any MCMC should account for this important restriction. We construct a fully automatic and efficient MCMC strategy for quantitative learning for such models that handles these problems. While the prior is expressed in terms of the marginal log-linear interactions, we build an MCMC algorithm that employs a proposal on the probability parameter space. The corresponding proposal on the marginal log-linear interactions is obtained via parameter transformation. We exploit a conditional conjugate setup to build an efficient proposal on probability parameters. The proposed methodology is illustrated by a simulation study and a real dataset. Full Article
probability Hyundai Aura Review: Beating Maruti Dzire a strong probability By www.financialexpress.com Published On :: 2020-01-28T11:16:00+05:30 Hyundai aims to make the Aura the sub-compact king of sedans in India and dethrone the Maruti Suzuki Dzire with BS6 petrol and diesel engines. But does the Aura have what it takes to beat the Dzire? Watch this video and find out. Full Article
probability High Dimensional Probability VIII : The Oaxaca Volume [Electronic book] / edited by Nathael Gozlan, Rafał Latała, Karim Lounici, Mokshay Madiman. By encore.st-andrews.ac.uk Published On :: Cham : Birkhäuser, [2019] Full Article
probability Probability and statistics with R / María Dolores Ugarte (Public University of Navarre, Pamplona, Navarre, Spain), Ana F. Militino (Public University of Navarre, Pamplona, Navarre, Spain), Alan T. Arnholt (Appalachian State University, Boone, North C By prospero.murdoch.edu.au Published On :: Ugarte, María Dolores, author Full Article
probability Miller & Freund's probability and statistics for engineers / Richard A. Johnson, University of Wisconsin-Madison By prospero.murdoch.edu.au Published On :: Johnson, Richard Arnold Full Article
probability Confidence, likelihood, probability : statistical inference with confidence distributions / Tore Schweder (University of Oslo), Nils Lid Hjort (University of Oslo) By prospero.murdoch.edu.au Published On :: Schweder, Tore, author Full Article
probability Probability and statistical inference / Robert V. Hogg, Elliot A. Tanis, Dale L. Zimmerman By prospero.murdoch.edu.au Published On :: Hogg, Robert V., author Full Article
probability Probability & statistics for engineers & scientists / Ronald E. Walpole (Roanoke College), Raymond H. Myers (Virginia Tech), Sharon L. Myers (Radford University), Keying Ye (University of Texas at San Antonio) By prospero.murdoch.edu.au Published On :: Walpole, Ronald E., author Full Article
probability Probability & statistics with R for engineers and scientists / Michael Akritas (The Pennsylvania State University) By prospero.murdoch.edu.au Published On :: Akritas, Michael G., author Full Article
probability Probability and statistics in experimental physics / Byron P. Roe By prospero.murdoch.edu.au Published On :: Roe, Byron P., author Full Article
probability Applied statistics and probability for engineers / authors, Douglas C. Montgomery, George C. Runger By prospero.murdoch.edu.au Published On :: Montgomery, Douglas C., author Full Article
probability Probability theory and statistical inference: empirical modelling with observational data / Aris Spanos By library.mit.edu Published On :: Sun, 8 Mar 2020 07:47:17 EDT Dewey Library - QA273.S6875 2019 Full Article
probability Probability and statistics for data science: math + R + data / Norman Matloff By library.mit.edu Published On :: Sun, 8 Mar 2020 07:47:17 EDT Dewey Library - QA273.M38495 2020 Full Article
probability Probability: a lively introduction / Henk Tijms By library.mit.edu Published On :: Sun, 26 Apr 2020 06:32:35 EDT Barker Library - QA273.2.T55 2018 Full Article
probability Janus-Faced Probability [electronic resource] / by Paolo Rocchi By darius.uleth.ca Published On :: Cham : Springer International Publishing : Imprint: Springer, 2014 Full Article
probability Geometric Modeling in Probability and Statistics [electronic resource] / by Ovidiu Calin, Constantin Udrişte By darius.uleth.ca Published On :: Cham : Springer International Publishing : Imprint: Springer, 2014 Full Article
probability Electronic communications in probability [electronic resource] By darius.uleth.ca Published On :: Seattle : University of Washington, 1996- Full Article
probability Electronic journal of probability [electronic resource] By darius.uleth.ca Published On :: [Seattle, Wash.] : Electronic Journal of Probability and Electronic Communications in Probability, 1995- Full Article
probability Probability theory on semihypergroups By digital.lib.usf.edu Published On :: Sat, 15 Feb 2014 18:23:13 -0400 Full Article
probability Study of laplace and related probability distributions and their applications By digital.lib.usf.edu Published On :: Sat, 15 Feb 2014 18:32:26 -0400 Full Article
probability Application of an improved transition probability matrix based crack rating prediction methodology in Forida's highway network By digital.lib.usf.edu Published On :: Sat, 15 Feb 2014 18:49:27 -0400 Full Article
probability BJP to discuss probability of parting ways with ally Sena tomorrow By indianexpress.com Published On :: Wed, 14 Oct 2015 07:22:41 +0000 Full Article DO NOT USE Maharashtra India