03834nam a22004695i 4500001001800000003000900018005001700027007001500044008004100059020001800100024003500118050001400153072001600167072002300183072001500206100008500221245017300306250001800479264007200497300006900569336002600638337002600664338003600690347002400726490006200750505074600812520130801558650001602866650001902882650002502901650003602926650002402962650002702986700007503013710003403088773002603122776003603148776003603184776003603220830006203256856004603318978-981-99-9363-5DE-He21320251030111810.0cr nn 008mamaa240408s2024    si |    s    |||| 0|eng d  a97898199936357 a10.1007/978-981-99-9363-52doi 4aQA276-280 7aPBT2bicssc 7aMAT0290002bisacsh 7aPBT2thema1 aSelvamuthu, Dharmaraja.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut10aIntroduction to Probability, Statistical Methods, Design of Experiments and Statistical Quality Controlh[electronic resource] /cby Dharmaraja Selvamuthu, Dipayan Das.  a2nd ed. 2024. 1aSingapore :bSpringer Nature Singapore :bImprint: Springer,c2024.  aXXVIII, 609 p. 150 illus., 73 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda1 aUniversity Texts in the Mathematical Sciences,x2731-93260 aChapter 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. .  aThis 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. 0aStatistics. 0aProbabilities. 0aExperimental design.14aStatistical Theory and Methods.24aProbability Theory.24aDesign of Experiments.1 aDas, Dipayan.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut2 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978981999362808iPrinted edition:z978981999364208iPrinted edition:z9789819993659 0aUniversity Texts in the Mathematical Sciences,x2731-932640uhttps://doi.org/10.1007/978-981-99-9363-5