A Replication Approach To Interval Estimation In Sumulation PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download A Replication Approach To Interval Estimation In Sumulation PDF full book. Access full book title A Replication Approach To Interval Estimation In Sumulation.

Introduction to the New Statistics

Introduction to the New Statistics
Author: Geoff Cumming
Publisher: Taylor & Francis
Total Pages: 611
Release: 2024-03-21
Genre: Psychology
ISBN: 1003849016

Download Introduction to the New Statistics Book in PDF, ePub and Kindle

This fully revised and updated second edition is an essential introduction to inferential statistics. It is the first introductory statistics text to use an estimation approach from the start and also to explain the new and exciting Open Science practices, which encourage replication and enhance the trustworthiness of research. The estimation approach, with meta-analysis (“the new statistics”), is exactly what’s needed for Open Science. Key features of this new edition include: Even greater prominence for Open Science throughout the book. Students easily understand basic Open Science practices and are guided to use them in their own work. There is discussion of the latest developments now being widely adopted across science and medicine. Integration of new open-source esci (Estimation Statistics with Confidence Intervals) software, running in jamovi. This is ideal for the book and extends seamlessly to what’s required for more advanced courses, and also by researchers. See www.thenewstatistics.com/itns/esci/jesci/. Colorful interactive simulations, including the famous dances, to help make key statistical ideas intuitive. These are now freely available through any browser. See www.esci.thenewstatistics.com/. Coverage of both estimation and null hypothesis significance testing (NHST) approaches, with full guidance on how to translate between the two. Effective learning strategies and pedagogical features to promote critical thinking, comprehension and retention Designed for introduction to statistics, data analysis, or quantitative methods courses in psychology, education, and other social and health sciences, researchers interested in understanding Open Science and the new statistics will also appreciate this book. No familiarity with introductory statistics is assumed.


Performance Evaluation by Simulation and Analysis with Applications to Computer Networks

Performance Evaluation by Simulation and Analysis with Applications to Computer Networks
Author: Ken Chen
Publisher: John Wiley & Sons
Total Pages: 316
Release: 2015-02-02
Genre: Computers
ISBN: 111900621X

Download Performance Evaluation by Simulation and Analysis with Applications to Computer Networks Book in PDF, ePub and Kindle

This book is devoted to the most used methodologies for performance evaluation: simulation using specialized software and mathematical modeling. An important part is dedicated to the simulation, particularly in its theoretical framework and the precautions to be taken in the implementation of the experimental procedure. These principles are illustrated by concrete examples achieved through operational simulation languages ​​(OMNeT ++, OPNET). Presented under the complementary approach, the mathematical method is essential for the simulation. Both methodologies based largely on the theory of probability and statistics in general and particularly Markov processes, a reminder of the basic results is also available.


An Interval Based Approach to Model Input Uncertainty in Discrete-event Simulation

An Interval Based Approach to Model Input Uncertainty in Discrete-event Simulation
Author: Ola Ghazi Y. Batarseh
Publisher:
Total Pages: 134
Release: 2010
Genre: Discrete-time systems
ISBN:

Download An Interval Based Approach to Model Input Uncertainty in Discrete-event Simulation Book in PDF, ePub and Kindle

The objective of this research is to increase the robustness of discrete-event simulation (DES) when input uncertainties associated models and parameters are present. Input uncertainties in simulation have different sources, including lack of data, conflicting information and beliefs, lack of introspection, measurement errors, and lack of information about dependency. A reliable solution is obtained from a simulation mechanism that accounts for these uncertainty components in simulation. An interval-based simulation (IBS) mechanism based on imprecise probabilities is proposed, where the statistical distribution parameters in simulation are intervals instead of precise real numbers. This approach incorporates variability and uncertainty in systems. In this research, a standard procedure to estimate interval parameters of probability distributions is developed based on the measurement of simulation robustness. New mechanisms based on the inverse transform to generate interval random variates are proposed. A generic approach to specify the required replication length to achieve a desired level of robustness is derived. Furthermore, three simulation clock advancement approaches in the interval-based simulation are investigated. A library of Java-based IBS toolkits that simulates queueing systems is developed to demonstrate the new proposed reliable simulation. New interval statistics for interval data analysis are proposed to support decision making. To assess the performance of the IBS, we developed an interval-based metamodel for automated material handling systems, which generates interval performance measures that are more reliable and computationally more efficient than traditional DES simulation results.