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Titlebook: Introduction to Probability, Statistical Methods, Design of Experiments and Statistical Quality Cont; Dharmaraja Selvamuthu,Dipayan Das Te

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發(fā)表于 2025-3-21 18:25:57 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Introduction to Probability, Statistical Methods, Design of Experiments and Statistical Quality Cont
編輯Dharmaraja Selvamuthu,Dipayan Das
視頻videohttp://file.papertrans.cn/475/474065/474065.mp4
概述Covers the statistical methods, the design of experiments, and statistical quality control.Supplies several practical and class-tested examples and end-of-chapter exercises.Includes R software and exa
叢書名稱University Texts in the Mathematical Sciences
圖書封面Titlebook: Introduction to Probability, Statistical Methods, Design of Experiments and Statistical Quality Cont;  Dharmaraja Selvamuthu,Dipayan Das Te
描述.This revised book provides an accessible presentation of concepts from probability theory, statistical methods, the design of experiments, and statistical quality control. It is shaped by the experience of the two teachers teaching statistical methods and concepts to engineering students. Practical examples and end-of-chapter exercises are the highlights of the text, as they are purposely selected from different fields. Statistical principles discussed in the book have a great relevance in several disciplines like economics, commerce, engineering, medicine, health care, agriculture, biochemistry, and textiles to mention a few..Organised into 16 chapters, the revised book discusses four major topics—probability theory, statistical methods, the design of experiments, and statistical quality control. A large number of students with varied disciplinary backgrounds need a course in basics of statistics, the design of experiments and statistical quality control at an introductory level to pursue their discipline of interest. No previous knowledge of probability or statistics is assumed, but an understanding of calculus is a prerequisite. The whole book also serves as a master level intr
出版日期Textbook 2024Latest edition
關(guān)鍵詞data representation; descriptive statistics; sampling distributions; point estimation; Neyman-Pearson th
版次2
doihttps://doi.org/10.1007/978-981-99-9363-5
isbn_softcover978-981-99-9365-9
isbn_ebook978-981-99-9363-5Series ISSN 2731-9318 Series E-ISSN 2731-9326
issn_series 2731-9318
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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沙發(fā)
發(fā)表于 2025-3-21 20:47:59 | 只看該作者
University Texts in the Mathematical Scienceshttp://image.papertrans.cn/i/image/474065.jpg
板凳
發(fā)表于 2025-3-22 03:46:01 | 只看該作者
Random Variables and ExpectationsRandom experiments have sample spaces may not consist of numbers. For instance, in a coin-tossing experiment, the sample space consists of the outcomes “head" and “tail”, i.e., .Since statistical methods primarily rely on numerical data, it becomes necessary to represent the outcomes of the sample space mathematically.
地板
發(fā)表于 2025-3-22 07:12:15 | 只看該作者
Standard DistributionsThis chapter delves into some discrete and continuous distributions that are frequently encountered, while also examining their key characteristics.
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發(fā)表于 2025-3-22 09:37:30 | 只看該作者
Response Surface MethodologyResponse surface methodologyor in short RSM is a collection of mathematical and statistical tools and techniques that are useful in developing, understanding, and optimizing processes and products. Using this methodology, the responses that are influenced by several variables can be modeled, analyzed, and optimized.
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發(fā)表于 2025-3-22 13:00:38 | 只看該作者
978-981-99-9365-9The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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發(fā)表于 2025-3-22 17:22:14 | 只看該作者
Introduction to Probability, Statistical Methods, Design of Experiments and Statistical Quality Cont978-981-99-9363-5Series ISSN 2731-9318 Series E-ISSN 2731-9326
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發(fā)表于 2025-3-23 04:24:19 | 只看該作者
Limiting Distributionsof this, it is crucial to research the asymptotic behavior of r.v. sequences. The weak law of large numbers, the strong law of large numbers, and the central limit theorem (CLT), are some of the most significant results within the theory of limit theorems that are covered in this chapter.
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發(fā)表于 2025-3-23 06:33:47 | 只看該作者
Testing of Hypothesisistribution, based on a random sample. Instead of finding an estimate for the parameter, we shall often find it convenient to hypothesize a value for it and then use the information from the sample to confirm or refute the hypothesized value.
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