Basic experimental strategies and data analysis for science and engineering:
Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Table of Contents -- List of Figures -- List of Tables -- Preface -- Author Bios -- 1: Strategies for Experimentation with Multiple Factors -- 1.1 Introduction -- 1.2 Some Definitions -- 1.3 Classical Versus Statistical Approaches...
Gespeichert in:
1. Verfasser: | |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Boca Raton ; London ; New York
CRC Press
2017
|
Schlagworte: | |
Online-Zugang: | BTU01 FWS01 FWS02 |
Zusammenfassung: | Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Table of Contents -- List of Figures -- List of Tables -- Preface -- Author Bios -- 1: Strategies for Experimentation with Multiple Factors -- 1.1 Introduction -- 1.2 Some Definitions -- 1.3 Classical Versus Statistical Approaches to Experimentation -- 1.4 Why Experiment? (Analysis of Historical Data) -- 1.5 Diagnosing the Experimental Environment -- 1.6 Example of a Complete Experimental Program -- 1.6.1 Chemical Process System -- 1.6.2 Step One: Screening 1.6.3 Step Two: Crude Optimization -- 1.6.4 Step Three: Final Optimization -- 1.7 Good Design Requirements -- 1.8 Summary -- 1.8.1 Important Terms and Concepts -- 2: Statistics and Probability -- 2.1 Introduction -- 2.2 Graphical and Numerical Summaries of a Single Response-Variable -- 2.2.1 Dot Diagrams -- 2.2.2 Sample Mean, Variance, and Standard Deviation -- 2.2.3 Histograms -- 2.2.4 Five-Number Summaries and Boxplots -- 2.3 Graphical and Numerical Summaries of the Relation Between Variables -- 2.4 What to Expect from Theory 2.4.1 Probability Density Functions and Probability -- 2.4.2 Expected Values, Variance, and Standard Deviation -- 2.4.3 Normal Distribution -- 2.4.4 Central Limit Theorem and Distribution of Sample Means -- 2.5 Using Theory to Help Interpret Experimental Data -- 2.5.1 Comparing the Mean of Experimental Results to a Standard -- 2.5.2 Comparing the Means of Two Experimental Conditions -- 2.5.3 Comparing the Means of Several Experimental Conditions -- 2.5.4 Comparing Observed Data to the Normal Distribution -- 2.6 Summary -- 2.6.1 Important Equations |
Beschreibung: | Description based upon print version of record |
Beschreibung: | 1 Online-Ressource (xxv, 418 Seiten) Illustrationen, Diagramme |
ISBN: | 9781315374529 9781466512184 |
Internformat
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520 | 1 | |a Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Table of Contents -- List of Figures -- List of Tables -- Preface -- Author Bios -- 1: Strategies for Experimentation with Multiple Factors -- 1.1 Introduction -- 1.2 Some Definitions -- 1.3 Classical Versus Statistical Approaches to Experimentation -- 1.4 Why Experiment? (Analysis of Historical Data) -- 1.5 Diagnosing the Experimental Environment -- 1.6 Example of a Complete Experimental Program -- 1.6.1 Chemical Process System -- 1.6.2 Step One: Screening | |
520 | 1 | |a 1.6.3 Step Two: Crude Optimization -- 1.6.4 Step Three: Final Optimization -- 1.7 Good Design Requirements -- 1.8 Summary -- 1.8.1 Important Terms and Concepts -- 2: Statistics and Probability -- 2.1 Introduction -- 2.2 Graphical and Numerical Summaries of a Single Response-Variable -- 2.2.1 Dot Diagrams -- 2.2.2 Sample Mean, Variance, and Standard Deviation -- 2.2.3 Histograms -- 2.2.4 Five-Number Summaries and Boxplots -- 2.3 Graphical and Numerical Summaries of the Relation Between Variables -- 2.4 What to Expect from Theory | |
520 | 1 | |a 2.4.1 Probability Density Functions and Probability -- 2.4.2 Expected Values, Variance, and Standard Deviation -- 2.4.3 Normal Distribution -- 2.4.4 Central Limit Theorem and Distribution of Sample Means -- 2.5 Using Theory to Help Interpret Experimental Data -- 2.5.1 Comparing the Mean of Experimental Results to a Standard -- 2.5.2 Comparing the Means of Two Experimental Conditions -- 2.5.3 Comparing the Means of Several Experimental Conditions -- 2.5.4 Comparing Observed Data to the Normal Distribution -- 2.6 Summary -- 2.6.1 Important Equations | |
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Datensatz im Suchindex
DE-BY-FWS_katkey | 657582 |
---|---|
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any_adam_object | |
author | Lawson, John 1947- |
author_GND | (DE-588)14146514X (DE-588)1130664473 |
author_facet | Lawson, John 1947- |
author_role | aut |
author_sort | Lawson, John 1947- |
author_variant | j l jl |
building | Verbundindex |
bvnumber | BV044508351 |
classification_rvk | SK 840 ZQ 3100 |
collection | ZDB-30-PQE |
ctrlnum | (ZDB-7-TFC)9781315374529 (OCoLC)1005735659 (DE-599)GBV872509036 |
discipline | Mathematik Mess-/Steuerungs-/Regelungs-/Automatisierungstechnik / Mechatronik |
format | Electronic eBook |
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id | DE-604.BV044508351 |
illustrated | Not Illustrated |
indexdate | 2024-08-01T12:48:48Z |
institution | BVB |
isbn | 9781315374529 9781466512184 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029908199 |
oclc_num | 1005735659 |
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owner | DE-862 DE-BY-FWS DE-863 DE-BY-FWS DE-634 |
owner_facet | DE-862 DE-BY-FWS DE-863 DE-BY-FWS DE-634 |
physical | 1 Online-Ressource (xxv, 418 Seiten) Illustrationen, Diagramme |
psigel | ZDB-30-PQE ebook |
publishDate | 2017 |
publishDateSearch | 2017 |
publishDateSort | 2017 |
publisher | CRC Press |
record_format | marc |
spellingShingle | Lawson, John 1947- Basic experimental strategies and data analysis for science and engineering Datenanalyse (DE-588)4123037-1 gnd Versuchsplanung (DE-588)4078859-3 gnd Ingenieurwissenschaften (DE-588)4137304-2 gnd Experiment (DE-588)4015999-1 gnd Statistik (DE-588)4056995-0 gnd |
subject_GND | (DE-588)4123037-1 (DE-588)4078859-3 (DE-588)4137304-2 (DE-588)4015999-1 (DE-588)4056995-0 |
title | Basic experimental strategies and data analysis for science and engineering |
title_auth | Basic experimental strategies and data analysis for science and engineering |
title_exact_search | Basic experimental strategies and data analysis for science and engineering |
title_full | Basic experimental strategies and data analysis for science and engineering John Lawson (Brigham Young University, Provo, Utah, USA), John Erjavec (University of North Dakota, Grand Forks, USA) |
title_fullStr | Basic experimental strategies and data analysis for science and engineering John Lawson (Brigham Young University, Provo, Utah, USA), John Erjavec (University of North Dakota, Grand Forks, USA) |
title_full_unstemmed | Basic experimental strategies and data analysis for science and engineering John Lawson (Brigham Young University, Provo, Utah, USA), John Erjavec (University of North Dakota, Grand Forks, USA) |
title_short | Basic experimental strategies and data analysis for science and engineering |
title_sort | basic experimental strategies and data analysis for science and engineering |
topic | Datenanalyse (DE-588)4123037-1 gnd Versuchsplanung (DE-588)4078859-3 gnd Ingenieurwissenschaften (DE-588)4137304-2 gnd Experiment (DE-588)4015999-1 gnd Statistik (DE-588)4056995-0 gnd |
topic_facet | Datenanalyse Versuchsplanung Ingenieurwissenschaften Experiment Statistik |
work_keys_str_mv | AT lawsonjohn basicexperimentalstrategiesanddataanalysisforscienceandengineering AT erjavecjohn basicexperimentalstrategiesanddataanalysisforscienceandengineering |