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Introduction to probability, statistical methods, design of experiments and statistical quality control

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Introduction to probability, statistical methods, design of experiments and statistical quality control/ by Dharmaraja Selvamuthu, Dipayan Das.
作者:	Selvamuthu, Dharmaraja.
其他作者:	Das, Dipayan.
出版者:	Singapore :Springer Nature Singapore : : 2024.,
面頁冊數:	xxviii, 609 p. :ill., digital ;24 cm.
內容註:	Chapter 1. Introduction -- Chapter 2. Basic Concepts of Probability -- Chapter 3. Random Variable and Distribution Function -- Chapter 4. Standard Deviation -- Chapter 5. Multiple Random Variable and Joint Distribution -- Chapter 6. Limiting Distributions -- Chapter 7. Descriptive Statistics -- Chapter 8. Sampling Distributions -- Chapter 9. Estimation -- Chapter 10. Testing of Hypothesis -- Chapter 11. Analysis of Correlation and Regression -- Chapter 12. Single Factor Experimental Design -- Chapter 13. Multi-Factor Experimental Designs -- Chapter 14. Response Surface Methodology -- Chapter 15. Acceptance Sampling -- Chapter 16. Control Charts. Appendix A. Statistical Tables -- Appendix B. Introduction to the R Software Program.
Contained By:	Springer Nature eBook
標題:	Mathematical statistics. -
電子資源:	https://doi.org/10.1007/978-981-99-9363-5
ISBN:	9789819993635

Introduction to probability, statistical methods, design of experiments and statistical quality control
Selvamuthu, Dharmaraja.

Introduction to probability, statistical methods, design of experiments and statistical quality control[electronic resource] /by Dharmaraja Selvamuthu, Dipayan Das. - Second edition. - Singapore :Springer Nature Singapore :2024. - xxviii, 609 p. :ill., digital ;24 cm. - University texts in the mathematical sciences,2731-9326. - University texts in the mathematical sciences..

Chapter 1. Introduction -- Chapter 2. Basic Concepts of Probability -- Chapter 3. Random Variable and Distribution Function -- Chapter 4. Standard Deviation -- Chapter 5. Multiple Random Variable and Joint Distribution -- Chapter 6. Limiting Distributions -- Chapter 7. Descriptive Statistics -- Chapter 8. Sampling Distributions -- Chapter 9. Estimation -- Chapter 10. Testing of Hypothesis -- Chapter 11. Analysis of Correlation and Regression -- Chapter 12. Single Factor Experimental Design -- Chapter 13. Multi-Factor Experimental Designs -- Chapter 14. Response Surface Methodology -- Chapter 15. Acceptance Sampling -- Chapter 16. Control Charts. Appendix A. Statistical Tables -- Appendix B. Introduction to the R Software Program.

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 introductory course in all the three topics, as required in textile engineering or industrial engineering.

ISBN: 9789819993635

Standard No.: 10.1007/978-981-99-9363-5doiSubjects--Topical Terms:

516858
Mathematical statistics.

LC Class. No.: QA276

Dewey Class. No.: 519.5

Introduction to probability, statistical methods, design of experiments and statistical quality control
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505 0 $a Chapter 1. Introduction -- Chapter 2. Basic Concepts of Probability -- Chapter 3. Random Variable and Distribution Function -- Chapter 4. Standard Deviation -- Chapter 5. Multiple Random Variable and Joint Distribution -- Chapter 6. Limiting Distributions -- Chapter 7. Descriptive Statistics -- Chapter 8. Sampling Distributions -- Chapter 9. Estimation -- Chapter 10. Testing of Hypothesis -- Chapter 11. Analysis of Correlation and Regression -- Chapter 12. Single Factor Experimental Design -- Chapter 13. Multi-Factor Experimental Designs -- Chapter 14. Response Surface Methodology -- Chapter 15. Acceptance Sampling -- Chapter 16. Control Charts. Appendix A. Statistical Tables -- Appendix B. Introduction to the R Software Program.
520 $a 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 introductory course in all the three topics, as required in textile engineering or industrial engineering.
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