Data Driven Statistical Methods PDF Download
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Author | : Peter Sprent |
Publisher | : Routledge |
Total Pages | : 471 |
Release | : 2019-12-06 |
Genre | : Mathematics |
ISBN | : 1351456555 |
Download Data Driven Statistical Methods Book in PDF, ePub and Kindle
Calculations once prohibitively time-consuming can be completed in microseconds by modern computers. This has resulted in dramatic shifts in emphasis in applied statistics. Not only has it freed us from an obsession with the 5% and 1% significance levels imposed by conventional tables but many exact estimation procedures based on randomization tests are now as easy to carry out as approximations based on normal distribution theory. In a wider context it has facilitated the everyday use of tools such as the bootstrap and robust estimation methods as well as diagnostic tests for pinpointing or for adjusting possible aberrations or contamination that may otherwise be virtually undetectable in complex data sets. Data Driven Statistical Methods provides an insight into modern developments in statistical methodology using examples that highlight connections between these techniques as well as their relationship to other established approaches. Illustration by simple numerical examples takes priority over abstract theory. Examples and exercises are selected from many fields ranging from studies of literary style to analysis of survival data from clinical files, from psychological tests to interpretation of evidence in legal cases. Users are encouraged to apply the methods to their own or other data sets relevant to their fields of interest. The book will appeal both to lecturers giving undergraduate mainstream or service courses in statistics and to newly-practising statisticians or others concerned with data interpretation in any discipline who want to make the best use of modern statistical computer software.
Author | : Peter Sprent |
Publisher | : Routledge |
Total Pages | : 406 |
Release | : 2019-12-06 |
Genre | : Mathematics |
ISBN | : 1351456563 |
Download Data Driven Statistical Methods Book in PDF, ePub and Kindle
Calculations once prohibitively time-consuming can be completed in microseconds by modern computers. This has resulted in dramatic shifts in emphasis in applied statistics. Not only has it freed us from an obsession with the 5% and 1% significance levels imposed by conventional tables but many exact estimation procedures based on randomization tests are now as easy to carry out as approximations based on normal distribution theory. In a wider context it has facilitated the everyday use of tools such as the bootstrap and robust estimation methods as well as diagnostic tests for pinpointing or for adjusting possible aberrations or contamination that may otherwise be virtually undetectable in complex data sets. Data Driven Statistical Methods provides an insight into modern developments in statistical methodology using examples that highlight connections between these techniques as well as their relationship to other established approaches. Illustration by simple numerical examples takes priority over abstract theory. Examples and exercises are selected from many fields ranging from studies of literary style to analysis of survival data from clinical files, from psychological tests to interpretation of evidence in legal cases. Users are encouraged to apply the methods to their own or other data sets relevant to their fields of interest. The book will appeal both to lecturers giving undergraduate mainstream or service courses in statistics and to newly-practising statisticians or others concerned with data interpretation in any discipline who want to make the best use of modern statistical computer software.
Author | : Fouzi Harrou |
Publisher | : Elsevier |
Total Pages | : 330 |
Release | : 2020-07-03 |
Genre | : Technology & Engineering |
ISBN | : 0128193662 |
Download Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches Book in PDF, ePub and Kindle
Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches tackles multivariate challenges in process monitoring by merging the advantages of univariate and traditional multivariate techniques to enhance their performance and widen their practical applicability. The book proceeds with merging the desirable properties of shallow learning approaches – such as a one-class support vector machine and k-nearest neighbours and unsupervised deep learning approaches – to develop more sophisticated and efficient monitoring techniques. Finally, the developed approaches are applied to monitor many processes, such as waste-water treatment plants, detection of obstacles in driving environments for autonomous robots and vehicles, robot swarm, chemical processes (continuous stirred tank reactor, plug flow rector, and distillation columns), ozone pollution, road traffic congestion, and solar photovoltaic systems. Uses a data-driven based approach to fault detection and attribution Provides an in-depth understanding of fault detection and attribution in complex and multivariate systems Familiarises you with the most suitable data-driven based techniques including multivariate statistical techniques and deep learning-based methods Includes case studies and comparison of different methods
Author | : Concha Bielza |
Publisher | : Cambridge University Press |
Total Pages | : 709 |
Release | : 2020-11-26 |
Genre | : Computers |
ISBN | : 110849370X |
Download Data-Driven Computational Neuroscience Book in PDF, ePub and Kindle
Trains researchers and graduate students in state-of-the-art statistical and machine learning methods to build models with real-world data.
Author | : Georgi Zdravkov Georgiev |
Publisher | : |
Total Pages | : 302 |
Release | : 2019-09-28 |
Genre | : |
ISBN | : 9781694079725 |
Download Statistical Methods in Online A/B Testing Book in PDF, ePub and Kindle
"Statistical Methods in Online A/B Testing" is a comprehensive guide to statistics in online controlled experiments, a.k.a. A/B tests, that tackles the difficult matter of statistical inference in a way accessible to readers with little to no prior experience with it. Each concept is built from the ground up, explained thoroughly, and illustrated with practical examples from website testing. The presentation is straight to the point and practically oriented so you can apply the takeaways in your daily work.It is a must-read for anyone looking for a deep understanding of how to make data-driven business decisions through experimentation: conversion rate optimizers, product managers, growth experts, data analysts, marketing managers, experts in user experience and design. The new research presented and the fresh perspective on how to apply statistics and experimentation to achieve business goals make for an interesting read even for experienced statisticians.The book deals with scientific methods, but their introductions and explanations are grounded in the business goals they help achieve, such as innovating under controlled risk, and estimating the effect of proposed business actions before committing to them. While the book doesn't shy away from math and formulas, it is to the extent to which these are essential for understanding and applying the underlying concepts. The presentation is friendly to readers with little to no prior knowledge in statistics. Artificial and impractical examples like dice rolling and betting are absent, instead statistical concepts are illustrated through scenarios which might well be mistaken with the last couple of A/B tests you managed.This book also doesn't shy away from the fact that much of the current statistical theory and practice in online A/B testing is misguided, misinterpreted, or misapplied. It also addresses the issue of blind copying of scientific applications without due consideration of the unique features of online business, which is widespread. The book will help you avoid these malpractices by explicitly pointing out frequent mistakes, while also helping you align your usage of statistics and experimentation with any business goals you might want to pursue.
Author | : Jose Nathan Kutz |
Publisher | : |
Total Pages | : 657 |
Release | : 2013-08-08 |
Genre | : Computers |
ISBN | : 0199660336 |
Download Data-Driven Modeling & Scientific Computation Book in PDF, ePub and Kindle
Combining scientific computing methods and algorithms with modern data analysis techniques, including basic applications of compressive sensing and machine learning, this book develops techniques that allow for the integration of the dynamics of complex systems and big data. MATLAB is used throughout for mathematical solution strategies.
Author | : Mario Vanhoucke |
Publisher | : Apress |
Total Pages | : 164 |
Release | : 2018-03-27 |
Genre | : Business & Economics |
ISBN | : 1484234987 |
Download The Data-Driven Project Manager Book in PDF, ePub and Kindle
Discover solutions to common obstacles faced by project managers. Written as a business novel, the book is highly interactive, allowing readers to participate and consider options at each stage of a project. The book is based on years of experience, both through the author's research projects as well as his teaching lectures at business schools. The book tells the story of Emily Reed and her colleagues who are in charge of the management of a new tennis stadium project. The CEO of the company, Jacob Mitchell, is planning to install a new data-driven project management methodology as a decision support tool for all upcoming projects. He challenges Emily and her team to start a journey in exploring project data to fight against unexpected project obstacles. Data-driven project management is known in the academic literature as “dynamic scheduling” or “integrated project management and control.” It is a project management methodology to plan, monitor, and control projects in progress in order to deliver them on time and within budget to the client. Its main focus is on the integration of three crucial aspects, as follows: Baseline Scheduling: Plan the project activities to create a project timetable with time and budget restrictions. Determine start and finish times of each project activity within the activity network and resource constraints. Know the expected timing of the work to be done as well as an expected impact on the project’s time and budget objectives. Schedule Risk Analysis: Analyze the risk of the baseline schedule and its impact on the project’s time and budget. Use Monte Carlo simulations to assess the risk of the baseline schedule and to forecast the impact of time and budget deviations on the project objectives. Project Control: Measure and analyze the project’s performance data and take actions to bring the project on track. Monitor deviations from the expected project progress and control performance in order to facilitate the decision-making process in case corrective actions are needed to bring projects back on track. Both traditional Earned Value Management (EVM) and the novel Earned Schedule (ES) methods are used. What You'll Learn Implement a data-driven project management methodology (also known as "dynamic scheduling") which allows project managers to plan, monitor, and control projects while delivering them on time and within budget Study different project management tools and techniques, such as PERT/CPM, schedule risk analysis (SRA), resource buffering, and earned value management (EVM) Understand the three aspects of dynamic scheduling: baseline scheduling, schedule risk analysis, and project control Who This Book Is For Project managers looking to learn data-driven project management (or "dynamic scheduling") via a novel, demonstrating real-time simulations of how project managers can solve common project obstacles
Author | : Susan Rovezzi Carroll |
Publisher | : Scarecrow Press |
Total Pages | : 161 |
Release | : 2002-10-16 |
Genre | : Education |
ISBN | : 0810843226 |
Download Statistics Made Simple for School Leaders Book in PDF, ePub and Kindle
The chief executive officer of a corporation is not much different from a public school administrator. While CEOs base many of their decisions on data, for school administrators, this type of research may conjure up miserable memories of searching for information to meet a graduate school requirement. However, the value of data-based decision making will continue to escalate and the school community—students, teachers, parents and the general public—expect this information to come from their administrators. Administrators are called on to be accountable, but few are capable of presenting the mountain of data that they collect in a cohesive and strategic manner. Most statistical books are focused on statistical theory versus application, but Statistics Made Simple for School Leaders presents statistics in a simple, practical, conceptual, and immediately applicable manner. It enables administrators to take their data and manage it into strategic information so the results can be used for action plans that benefit the school system. The approach is 'user friendly' and leaves the reader with a confident can-do attitude to communicate results and plans to staff and the community.
Author | : Nuno Crato |
Publisher | : Springer |
Total Pages | : 346 |
Release | : 2018-10-02 |
Genre | : Political Science |
ISBN | : 3319784617 |
Download Data-Driven Policy Impact Evaluation Book in PDF, ePub and Kindle
In the light of better and more detailed administrative databases, this open access book provides statistical tools for evaluating the effects of public policies advocated by governments and public institutions. Experts from academia, national statistics offices and various research centers present modern econometric methods for an efficient data-driven policy evaluation and monitoring, assess the causal effects of policy measures and report on best practices of successful data management and usage. Topics include data confidentiality, data linkage, and national practices in policy areas such as public health, education and employment. It offers scholars as well as practitioners from public administrations, consultancy firms and nongovernmental organizations insights into counterfactual impact evaluation methods and the potential of data-based policy and program evaluation.
Author | : Jay Jacobs |
Publisher | : John Wiley & Sons |
Total Pages | : 354 |
Release | : 2014-02-24 |
Genre | : Computers |
ISBN | : 1118793722 |
Download Data-Driven Security Book in PDF, ePub and Kindle
Uncover hidden patterns of data and respond with countermeasures Security professionals need all the tools at their disposal to increase their visibility in order to prevent security breaches and attacks. This careful guide explores two of the most powerful data analysis and visualization. You'll soon understand how to harness and wield data, from collection and storage to management and analysis as well as visualization and presentation. Using a hands-on approach with real-world examples, this book shows you how to gather feedback, measure the effectiveness of your security methods, and make better decisions. Everything in this book will have practical application for information security professionals. Helps IT and security professionals understand and use data, so they can thwart attacks and understand and visualize vulnerabilities in their networks Includes more than a dozen real-world examples and hands-on exercises that demonstrate how to analyze security data and intelligence and translate that information into visualizations that make plain how to prevent attacks Covers topics such as how to acquire and prepare security data, use simple statistical methods to detect malware, predict rogue behavior, correlate security events, and more Written by a team of well-known experts in the field of security and data analysis Lock down your networks, prevent hacks, and thwart malware by improving visibility into the environment, all through the power of data and Security Using Data Analysis, Visualization, and Dashboards.