1: Studi lucreziani / Carlo Giussani

• Record Nr.: UNICASTSA0686109
• Autore: Lucretius Carus, Titus
• Pubbl/distr/stampa: Torino, : Loescher, 1896
• Descrizione fisica: LXXXII, 284 p. ; 20 cm.
• Lingua di pubblicazione: Italiano; Greco antico
• Formato: Materiale a stampa
• Livello bibliografico: Monografia

Introductory statistics for engineering experimentation [[electronic resource] /] / Peter R. Nelson, Marie Coffin, Karen A.F. Copeland

• Record Nr.: UNINA9910784567603321
• Autore: Nelson Peter R
• Pubbl/distr/stampa: Amsterdam ; ; Boston, : Elsevier/Academic Press, c2003
• ISBN: 1-281-00553-3; 9786611005535; 0-08-049165-0
• Descrizione fisica: 1 online resource (527 p.)
• Altri autori (Persone): NelsonPeter R; CoffinMarie; CopelandKaren A. F
• Disciplina: 620/.007/27
• Soggetti: Engineering - Statistical methods; Engineering - Experiments
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references (p. 508-510) and index.
• Nota di contenuto: Front Cover; Introductory Statistics for Engineering Experimentation; Copyright Page; Contents; Preface; Chapter 1. Introduction; Variability; Experimental Design; Random Sampling; Randomization; Replication; ; Problems; Chapter 2. Summarizing Data; 2.1 Simple Graphical Techniques; 2.2 Numerical Summaries and Box Plots; 2.3 Graphical Tools for Designed Experiments; 2.4 Chapter Problems; Chapter 3. Models for Experiment Outcomes; 3.1 Models for Single-Factor Experiments; 3.2 Models for Two-Factor Factorial Experiments; 3.3 Models for Bivariate Data; 3.4 Models for Multivariate Data; 3.5 Assessing the Fit of a Model 3.6 Chapter Problems; Chapter 4. Models for the Random Error; 4.1 Random Variables; 4.2 Important Discrete Distributions; 4.3 Important Continuous Distributions; 4.4 Assessing the Fit of a Distribution; 4.5 Chapter Problems; Chapter 5. Inference for a Single Population; 5.1 Central Limit Theorem; 5.2 A Confidence Interval for μ; 5.3 Prediction and Tolerance Intervals; 5.4 Hypothesis Tests; 5.5 Inference for Binomial Populations; 5.6 Chapter Problems; Chapter 6. Comparing Two Populations; 6.1 Paired Samples; 6.2 Independent Samples; 6.3 Comparing Two Binomial Populations 6.4 Chapter Problems; Chapter 7. One-Factor Multi-Sample Experiments; 7.1 Basic Inference; 7.2 The Analysis of Means; 7.3 ANOM with Unequal Sample Sizes; 7.4 ANOM for Proportions; 7.5 The Analysis of Variance; 7.6 The Equal Variances Assumption; 7.7 Sample Sizes; 7.8 Chapter Problems; Chapter 8. Experiments with Two Factors; 8.1 Interaction; 8.2 More Than One Observation Per Cell; 8.3 Only One Observation per Cell; 8.4 Blocking to Reduce Variability; 8.5 Chapter Problems; Chapter 9. Multi-Factor Experiments; 9.1 ANOVA for Multi-Factor Experiments; 9.2 2k Factorial Designs 9.3 Fractional Factorial Designs; 9.4 Chapter Problems; Chapter 10. Inference for Regression Models; 10.1 Inference for a Regression Line; 10.2 Inference for Other Regression Models; 10.3 Chapter Problems; Chapter 11. Response Surface Methods; 11.1 First-Order Designs; 11.2 Second-Order Designs; 11.3 Chapter Problems; Chapter 12. Appendices; 12.1 Appendix A - Descriptions of Data Sets; 12.2 Appendix B - Tables; 12.3 Appendix C - Figures; 12.4 Appendix D - Sample Projects; Chapter 13. References; Index
• Sommario/riassunto: The Accreditation Board for Engineering and Technology (ABET) introduced a criterion starting with their 1992-1993 site visits that ""Students must demonstrate a knowledge of the application of statistics to engineering problems."" Since most engineering curricula are filled with requirements in their own discipline, they generally do not have time for a traditional two semesters of probability and statistics. Attempts to condense that material into a single semester often results in so much time being spent on probability that the statistics useful for designing and analyzing engineer