Last edited by Samut
Monday, October 19, 2020 | History

7 edition of Fundamentals of Statistics with Fuzzy Data (Studies in Fuzziness and Soft Computing) found in the catalog.

Fundamentals of Statistics with Fuzzy Data (Studies in Fuzziness and Soft Computing)

by Hung T. Nguyen

  • 175 Want to read
  • 6 Currently reading

Published by Springer .
Written in English

    Subjects:
  • Probability & statistics,
  • Mathematics,
  • Computer Books: General,
  • Computers,
  • Probability & Statistics - General,
  • Applied,
  • Artificial Intelligence - General,
  • Fuzzy Logic,
  • Mathematics / Applied,
  • Statistics,
  • Data Modeling & Design,
  • Fuzzy statistics

  • The Physical Object
    FormatHardcover
    Number of Pages195
    ID Numbers
    Open LibraryOL9056248M
    ISBN 103540316957
    ISBN 109783540316954

    Fundamentals of Statistics is the brief version of Statistics: Informed Decisions Using Data. With Fundamentals of Statistics, author and instructor Mike Sullivan III draws on his passion for statistics and teaching to provide the tools needed to see that statistics is connected, not only within individual concepts, but also in the world at :// Fundamentals of Statistics is the brief version of Statistics: Informed Decisions Using Data. With Fundamentals of Statistics, author and instructor Mike Sullivan III draws on his passion for statistics Mike has built this book in the classroom using feedback from his students. He is well Of Statistics 5th.

    Statistical methods are used at each step in an applied machine learning project. This means it is important to have a strong grasp of the fundamentals of the key findings from statistics and a working knowledge of relevant statistical methods. Unfortunately, statistics is not covered in many computer science and software engineering degree :// Fundamentals of Predictive Analytics with JMP bridges the gap between courses on basic statistics, which focus on univariate and bivariate analysis, and courses on data mining/predictive analytics. This book provides the technical knowledge and problem-solving skills needed to perform real data multivariate ://

    Fundamentals of Statistics, with Access Code: Informed Decisions Using Data Books a la Carte are unbound, three-hole-punch versions of the textbook. This lower cost option is easy to transport and comes with same access code or media that would be packaged with the bound   The main mathematical model for fuzzy data is a fuzzy random variable. A good theoretical treatment is in the Li-Ogura-Kreinovich book (Limit Theorems and Applications of Set-Valued and Fuzzy Set-Valued Random Variables). A less mathematical, yet still theoretical book is Bandemer and Nather's Fuzzy Data Analysis (however note the date).


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Fundamentals of Statistics with Fuzzy Data (Studies in Fuzziness and Soft Computing) by Hung T. Nguyen Download PDF EPUB FB2

Theories of fuzzy logic and of random closed sets are used as basic ingredients in building statistical concepts and procedures in the context of imprecise data, including coarse data analysis.

The monograph also aims at motivating statisticians to look at fuzzy statistics to enlarge the domain of applicability of statistics in :// This research monograph presents basic foundational aspects for a theory of statistics with fuzzy data, together with a set of practical applications.

Fuzzy data are modeled as observations from random fuzzy sets. Theories of fuzzy logic and of random closed sets are used as basic ingredients  › Mathematics › Probability Theory and Stochastic Processes.

This book presents basic aspects for a theory of statistics with fuzzy data, together with a set of practical applications. The book aims at motivating statisticians to examine fuzzy statistics to Read more Get this from a library.

Fundamentals of statistics with fuzzy data. [Hung T Nguyen; Berlin Wu] -- "This research monograph presents basic foundational aspects for a theory of statistics with fuzzy data, together with a set of practical applications.

Fuzzy data are modeled as observations from   Theories of fuzzy logic and of random closed sets are used as basic ingredients in building statistical concepts and procedures in the context of imprecise data, including coarse data analysis.

This book presents basic aspects for a theory of statistics with fuzzy data, together with a   文件名: Fundamentals of Statistics with Fuzzy 附件大小: MB 有奖举报问题资料 下载通道游客无法下载, 注册 登录 付费注册 熟悉论坛请点击新手指南 下载说明 1.下载一个附件当天只会扣除您一次下载次数和一次流量费。 2.论坛支持迅雷和 Fundamentals of Statistics covers topics on the introduction, fundamentals, and science of statistics.

The book discusses the collection, organization and representation of numerical data; elementary probability; the binomial Poisson distributions; and the measures of central :// Fundamentals of Statistics is the brief version of Statistics: Informed Decisions Using Data.

With Fundamentals of Statistics, author and instructor Mike Sullivan III draws on his passion for statistics and teaching to provide the tools needed to see that statistics is connected, not only within individual concepts, but also in the world at  › Books › Science & Math › Mathematics. This very nicely done text is designed as a one-semester version of Prof.

Sullivan's "Statistics: Informed Decisions Using Data" for an introductory course in basic statistics. As you might surmise from the larger text's title, an important emphasis is gathering and understanding how to use  › Books › Science & Math › Mathematics.

Fundamentals of Statistics is the brief version of Statistics: Informed Decisions Using Data. With Fundamentals of Statistics, author and instructor Mike Sullivan III draws on his passion for statistics and teaching to provide the tools students need to see that statistics is connected, not only within individual concepts, but also in the world   Fundamentals of Statistics, 4th Edition.

Making Informed Decisions: Mike Sullivan helps students connect statistical concepts with their everyday lives, teaching them to think critically and make informed decisions. Putting It Together–found in chapter openers, sections, and exercises–connects concepts from different chapters to show statistics as a whole rather than a series of The study carefully reveals how to use fuzzy statistics in people's time management effectiveness of fuzzy time allocation and management assessments.

Empirical studies demonstrate how to measure fuzzy data that can deal with trapezoid, triangular, and interval-valued data simultaneously and how to perform the nonparametric hypothesis ://    Many students are using our Free Statistics Lab Manual\rwhich loads into most spreadsheets.\rIt is really a Quick way to learn.\rIt is a stand alone but was designed to use with our free\rQuick Notes Statistics textbooks.\rThis textbook free pd\ Book   Fundamentals of Statistics is the brief version of Statistics: Informed Decisions Using Data.

With Fundamentals of Statistics, author and instructor Mike Sullivan III draws on his passion for statistics and teaching to provide the tools needed to see that statistics is connected, not only within individual concepts, but also in the world at :// The fuzzy approach to statistical analysis Article (PDF Available) in Computational Statistics & Data Analysis 51(1) November with 2, Reads How we measure 'reads' /_The_fuzzy_approach_to_statistical_analysis.

An exceptionally student-focused introduction to data analytics featuring traditionally-hard topics that are made learnable via hundreds of animations and learning questions. Included statistics/probability background enables all students to succeed. R coding practices are provided throughout to allow students to experiment.

Commonly combined with “Statistics for Data Analytics“ and   not add to the utility of the textbook as a tool to learn basic fundamentals of the subject. Since the first edition was published, inthe technology of fuzzy set theory and its application to systems, using fuzzy logic, has moved rapidly.

Developments in other theories such as possibility theory and evidence theory (both being elements of سایت اساتید/fuzzy logic with engineering application. In the fourth chapter, the fundamentals of descriptive statistics, the neces-sary basis for the data processed. The –fth chapter deals with the estimation of parameters.

The sixth chapter is devoted to testing statistical hypotheses about the pa-rameters set. Seventh and eighth chapter discusses the issue of linear dependency –   the fundamentals of statistics and introduce you to concepts that are used throughout this book.

The Five Basic Words of Statistics The five words population, sample, parameter, statistic (singular), and variable form the basic vocabulary of statistics. You cannot learn much about statis-tics unless you first learn the meanings of these five :// Abstract.

As in Chapter 5, we view random fuzzy sets as generalizations of random closed sets on R d, or more generally on Hausdorff, locally compact, second countable topologicaltechnically speaking, the study of limit theorems for random fuzzy sets can be carried out by using α-level sets and results from limit theorems for random closed ://.

Part two (fuzzy estimation) is used in Chapters 22 and 25; and part 3 (fuzzy hypothesis testing) is employed in Chapters 24 and Fuzzy prediction is contained in Chapters 23 and A most important part of our models in fuzzy statistics is that we always start with a random sample producing crisp (non-fuzzy) ://For instance, Nguyen et al.

[2, 3] provided the fundamentals of statistics with fuzzy data. Hong and Hwang [ 4 ] established the correlation coefficient of intuitionistic fuzzy sets in probability space by using the generalization of fuzzy sets by Zadeh [ 5 ].The second approach to Statistics with fuzzy data is not based on the concept of a fuzzy random variable, but rather on the presupposition that there is a generic random v ariable U: Ω → R, a