Design of experiments with MINITAB
Most of the classic DOE books were written before DOE software was generally available, so the technical level that they assumed was that of the engineer or scientist who had to write his or her own analysis software. In this practical introduction to DOE, guided by the capabilities of the common so...
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| Main Author: | |
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| Format: | eBook |
| Language: | English |
| Published: |
Milwaukee, Wis. :
ASQ Quality Press,
[2005]
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| Subjects: | |
| ISBN: | 9781628703368 1628703369 0873896378 9780873896375 |
| Physical Description: | 1 online resource (xix, 499 pages) : illustrations |
Cover
Table of contents
| LEADER | 12553cam a2200457 i 4500 | ||
|---|---|---|---|
| 001 | kn-ocn883034936 | ||
| 003 | OCoLC | ||
| 005 | 20240717213016.0 | ||
| 006 | m o d | ||
| 007 | cr cn||||||||| | ||
| 008 | 140708s2005 wiua ob 001 0 eng d | ||
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| 020 | |a 9781628703368 |q (electronic bk.) | ||
| 020 | |a 1628703369 |q (electronic bk.) | ||
| 020 | |z 0873896378 | ||
| 020 | |z 9780873896375 | ||
| 035 | |a (OCoLC)883034936 |z (OCoLC)898037390 |z (OCoLC)961874322 |z (OCoLC)988728300 |z (OCoLC)999576698 | ||
| 100 | 1 | |a Mathews, Paul G., |d 1960- |1 https://id.oclc.org/worldcat/entity/E39PCjFkmMVtRXXK7QThyWKVvd | |
| 245 | 1 | 0 | |a Design of experiments with MINITAB / |c Paul G. Mathews. |
| 264 | 1 | |a Milwaukee, Wis. : |b ASQ Quality Press, |c [2005] | |
| 264 | 4 | |c ©2005 | |
| 300 | |a 1 online resource (xix, 499 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 504 | |a Includes bibliographical references (pages 489-490) and index. | ||
| 506 | |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty | ||
| 520 | 8 | |a Most of the classic DOE books were written before DOE software was generally available, so the technical level that they assumed was that of the engineer or scientist who had to write his or her own analysis software. In this practical introduction to DOE, guided by the capabilities of the common software packages, Paul Mathews presents the basic types and methods of designed experiments appropriate for engineers, scientists, quality engineers, and Six Sigma Black Belts and Master Black Belts. Although instructions in the use of MINITAB are detailed enough to provide effective guidance to a new MINITAB user, the book is still general enough to be very helpful to users of other DOE software packages. Every chapter contains many examples with detailed solutions including extensive output from MINITAB. Preview a sample chapter from this book along with the full table of contents by clicking here. You will need Adobe Acrobat to view this pdf file. | |
| 505 | 0 | |a Machine derived contents note: Table of Contents -- Preface xiii -- Acknowledgments xix -- Chapter 1 Graphical Presentation of Data 1 -- 1.1 Introduction 1 -- 1.2 Types of Data 1 -- 1.3 Bar Charts 2 -- 1.4 Histograms 3 -- 1.5 Dotplots 4 -- 1.6 Stem-and-Leaf Plots 4 -- 1.7 Box-and-Whisker Plots 5 -- 1.8 Scatter Plots 6 -- 1.9 Multi-Vari Charts 7 -- 1.10 An Introduction to MINITAB 9 -- 1.10.1 Starting MINITAB 9 -- 1.10.2 MINITAB Windows 9 -- 1.10.3 Using the Command Prompt 11 -- 1.10.4 Customizing MINITAB 11 -- 1.10.5 Entering Data 12 -- 1.10.6 Graphing Data 13 -- 1.10.7 Printing Data and Graphs 13 -- 1.10.8 Saving and Retrieving Information 14 -- 1.10.9 MINITAB Macros 15 -- 1.10.10 Summary of MINITAB Files 17 -- Chapter 2 Descriptive Statistics 19 -- 2.1 Introduction 19 -- 2.2 Selection of Samples 19 -- 2.3 Measures of Location 20 -- 2.3.1 The Median 20 -- 2.3.2 The Mean 21 -- 2.4 Measures of Variation 21 -- 2.4.1 The Range 21 -- 2.4.2 The Standard Deviation 22 -- 2.4.3 Degrees of Freedom 24 -- 2.4.4 The Calculating Form for the Standard Deviation 25 -- 2.5 The Normal Distribution 26 -- 2.6 Counting 30 -- 2.6.1 Multiplication of Choices 30 -- 2.6.2 Factorials 31 -- 2.6.3 Permutations 31 -- 2.6.4 Combinations 32 -- 2.7 MINITAB Commands to Calculate Descriptive Statistics 34 -- Chapter 3 Inferential Statistics 37 -- 3.1 Introduction 37 -- 3.2 The Distribution of Sample Means (Known) 38 -- 3.3 Confidence Interval for the Population Mean 41 -- 3.4 Hypothesis Test for One Sample Mean (Known) 42 -- 3.4.1 Hypothesis Test Rationale 42 -- 3.4.2 Decision Limits Based on Measurement Units 44 -- 3.4.3 Decision Limits Based on Standard (z) Units 45 -- 3.4.4 Decision Limits Based on the p Value 46 -- 3.4.5 Type 1 and Type 2 Errors 49 -- 3.4.6 One-Tailed Hypothesis Tests 51 -- 3.5 The Distribution of Sample Means (Unknown) 52 -- 3.5.1 Student's t Distribution 52 -- 3.5.2 A One-Sample Hypothesis Test for the Population Mean (Unknown) 54 -- 3.5.3 A Confidence Interval for the Population Mean (Unknown) 55 -- 3.6 Hypothesis Tests for Two Means 56 -- 3.6.1 Two Independent Samples (21 and 22 Known) 56 -- 3.6.2 Two Independent Samples (21 and 22 Unknown But Equal) 56 -- 3.6.3 Two Independent Samples (21 and 22 Unknown and Unequal) 58 -- 3.6.4 Paired Samples 59 -- 3.7 Inferences About One Variance (Optional) 61 -- 3.7.1 The Distribution of Sample Variances 61 -- 3.7.2 Hypothesis Test for One Sample Variance 63 -- 3.7.3 Confidence Interval for the Population Variance 64 -- 3.8 Hypothesis Tests for Two Sample Variances 65 -- 3.9 Quick Tests for the Two-Sample Location Problem 68 -- 3.9.1 Tukey's Quick Test 69 -- 3.9.2 Boxplot Slippage Tests 71 -- 3.10 General Procedure for Hypothesis Testing 73 -- 3.11 Testing for Normality 75 -- 3.11.1 Normal Probability Plots 75 -- 3.11.2 Quantitative Tests for Normality 78 -- 3.12 Hypothesis Tests and Confidence Intervals with MINITAB 79 -- 3.12.1 Confidence Interval for When is Known 79 -- 3.12.2 Hypothesis Tests for One Sample Mean (Known) 80 -- 3.12.3 Normal Probability Plots with MINITAB 82 -- 3.13 Sample-Size Calculations 82 -- 3.13.1 Sample-Size Calculations for Confidence Intervals 83 -- 3.13.2 Sample-Size Calculations for Hypothesis Tests 86 -- Chapter 4 DOE Language and Concepts 93 -- 4.1 Introduction 93 -- 4.2 Design of Experiments: Definition, Scope, and Motivation 93 -- 4.3 Experiment Defined 94 -- 4.4 Identification of Variables and Responses 94 -- 4.5 Types of Variables 96 -- 4.6 Types of Responses 97 -- 4.7 Interactions 98 -- 4.8 Types of Experiments 99 -- 4.9 Types of Models 100 -- 4.10 Selection of Variable Levels 105 -- 4.10.1 Qualitative Variable Levels 105 -- 4.10.2 Quantitative Variable Levels 105 -- 4.11 Nested Variables 106 -- 4.12 Covariates 107 -- 4.13 Definition of Design in Design of Experiments 107 -- 4.14 Types of Designs 108 -- 4.15 Randomization 109 -- 4.16 Replication and Repetition 113 -- 4.17 Blocking 114 -- 4.18 Confounding 117 -- 4.19 Occam's Razor and Effect Heredity 118 -- 4.20 Data Integrity and Ethics 119 -- 4.21 General Procedure for Experimentation 120 -- 4.21.1 Step 1: Cause-and-Effect Analysis 121 -- 4.21.2 Step 2: Document the Process 123 -- 4.21.3 Step 3: Write a Detailed Problem Statement 124 -- 4.21.4 Step 4: Preliminary Experimentation 125 -- 4.21.5 Step 5: Design the Experiment 126 -- 4.21.6 Step 6: Sample Size, Randomization, and Blocking 127 -- 4.21.7 Step 7: Run the Experiment 128 -- 4.21.8 Step 8: Analyze the Data 129 -- 4.21.9 Step 9: Interpret the Results 130 -- 4.21.10 Step 10: Run a Confirmation Experiment 130 -- 4.21.11 Step 11: Report the Experiment 131 -- 4.22 Experiment Documentation 136 -- 4.23 Why Experiments Go Bad 139 -- Chapter 5 Experiments for One-Way Classifications 143 -- 5.1 Introduction 143 -- 5.2 Analysis by Comparison of All Possible Pairs Means 144 -- 5.3 The Graphical Approach to ANOVA 145 -- 5.4 Introduction to ANOVA 147 -- 5.4.1 The ANOVA Rationale 147 -- 5.4.2 ANOVA Assumptions and Validation 150 -- 5.4.3 The ANOVA Table 154 -- 5.5 The Sum of Squares Approach to ANOVA Calculations 155 -- 5.6 The Calculating Forms for the Sums of Squares 159 -- 5.7 ANOVA for Unbalanced Experiments 160 -- 5.8 After ANOVA: Comparing the Treatment Means 161 -- 5.8.1 Introduction 161 -- 5.8.2 Bonferroni's Method 161 -- 5.8.3 Sidak's Method 163 -- 5.8.4 Duncan's Multiple Range Test 164 -- 5.8.5 Tukey's Multiple Comparisons Test 166 -- 5.8.6 Dunnett's Test 167 -- 5.9 ANOVA with MINITAB 167 -- 5.10 The Completely Randomized Design 172 -- 5.11 Analysis of Means 176 -- 5.12 Response Transformations 177 -- 5.12.1 Introduction 177 -- 5.12.2 The Logarithmic Transform 179 -- 5.12.3 Transforming Count Data 182 -- 5.12.4 Transforming Fraction Data 183 -- 5.12.5 The Rank Transform 184 -- 5.13 Sample Size for ANOVA 185 -- 5.14 Design Considerations for One-Way Classification Experiments 188 -- Chapter 6 Experiments for Multi-Way Classifications 191 -- 6.1 Introduction 191 -- 6.2 Rationale for the Two-Way ANOVA 192 -- 6.2.1 No-Way Classification 192 -- 6.2.2 One-Way Classification 193 -- 6.2.3 Two-Way Classification 196 -- 6.3 The Sums of Squares Approach for Two-Way ANOVA (One Replicate) 202 -- 6.4 Interactions 203 -- 6.5 Interpretation of Two-Way Experiments 210 -- 6.5.1 Introduction 210 -- 6.5.2 The Randomized Complete Block Design 211 -- 6.5.3 a Æ b Factorial Experiments 212 -- 6.6 Factorial Designs 213 -- 6.7 Multi-Way Classification ANOVA with MINITAB 215 -- 6.7.1 Two-Way ANOVA with MINITAB 215 -- 6.7.2 Creating and Analyzing Factorial Designs in MINITAB 221 -- 6.8 Design Considerations for Multi-Way Classification Designs 227 -- Chapter 7 Advanced ANOVA Topics 231 -- 7.1 Incomplete Factorial Designs 231 -- 7.2 Latin Squares and Other Squares 232 -- 7.3 Fixed and Random Variables 235 -- 7.3.1 One-Way Classification (Fixed Variable) 235 -- 7.3.2 Two-Way Classification (Both Variables Fixed) 237 -- 7.3.3 One-Way Classification (Random Variable) 238 -- 7.3.4 Two-Way Classification (One Fixed and One Random Variable) 241 -- 7.3.5 Two-Way Classification (Both Variables Random) 242 -- 7.4 Nested Designs 248 -- 7.4.1 Nested Variables 248 -- 7.4.2 Two-Stage Nested Design: B (A) 248 -- 7.4.3 Analysis of Nested Designs in MINITAB 249 -- 7.5 Power Calculations 250 -- 7.5.1 Comments on Notation 250 -- 7.5.2 General Introduction to Power Calculations 252 -- 7.5.3 Factorial Designs with All Variables Fixed 254 -- 7.5.4 Factorial Designs with Random Variables 256 -- 7.5.5 Nested Designs 261 -- 7.5.6 General Method to Determine the Power for a Fixed Variable 263 -- 7.5.7 General Method to Determine the Power for a Random Variable 266 -- Chapter 8 Linear Regression 273 -- 8.1 Introduction 273 -- 8.2 Linear Regression Rationale 273 -- 8.3 Regression Coefficients 277 -- 8.4 Linear Regression Assumptions 282 -- 8.5 Hypothesis Tests for Regression Coefficients 285 -- 8.6 Confidence Limits for the Regression Line 289 -- 8.7 Prediction Limits for the Observed Values 290 -- 8.8 Correlation 293 | |
| 505 | 0 | |a 8.8.1 The Coefficient of Determination 293 -- 8.8.2 The Correlation Coefficient 294 -- 8.8.3 Confidence Interval for the Correlation Coefficient 295 -- 8.8.4 The Adjusted Correlation Coefficient 298 -- 8.9 Linear Regression with MINITAB 299 -- 8.10 Transformations to Linear Form 301 -- 8.11 Polynomial Models 306 -- 8.12 Goodness of Fit Tests 309 -- 8.12.1 The Quadratic Model as a Test of Linear Goodness of Fit 309 -- 8.12.2 The Linear Lack of Fit Test 312 -- 8.13 Errors in Variables 316 -- 8.14 Weighted Regression 317 -- 8.15 Coded Variables 318 -- 8.16 Multiple Regression 320 -- 8.17 General Linear Models 327 -- 8.18 Sample Size Calculations for Linear Regression 337 -- 8.18.1 Sample Size to Determine the Slope with Specified Confidence 337 -- 8.18.2 Sample Size to Determine the Regression Constant with Specified Confidence 341 -- 8.18.3 Sample Size to Determine the Predicted Value of the Response with Specified Confidence 342 -- 8.18.4 Sample Size to Detect a Slope Different From Zero 343 -- 8.19 Design Considerations for Linear Regression 345 -- Chapter 9 Two-Level Factorial Experiments 347 -- 9.1 Introduction 347 -- 9.2 The 21 Factorial Experiment 347 -- 9.3 The 22 Factorial Experiment 351 -- 9.4 The 23 Factorial Design 362 -- 9.5 The Addition of Center Cells to 2k Designs 367 -- 9.6 General Procedure for Analysis of 2k Designs 370 -- 9.7 2k Factorial Designs in MINITAB 372 -- 9.7.1 Creating the 2k Designs in MINITAB 372 -- 9.7.2 Analyzing the 2k Factorial Designs with MINITAB 375. | |
| 590 | |a Knovel |b Knovel (All titles) | ||
| 630 | 0 | 0 | |a Minitab. |
| 630 | 0 | 7 | |a Minitab |2 fast |
| 650 | 0 | |a Statistical hypothesis testing. | |
| 650 | 0 | |a Experimental design. | |
| 650 | 0 | |a Science |x Statistical methods. | |
| 650 | 0 | |a Engineering |x Statistical methods. | |
| 655 | 7 | |a elektronické knihy |7 fd186907 |2 czenas | |
| 655 | 9 | |a electronic books |2 eczenas | |
| 776 | 0 | 8 | |i Print version: |a Mathews, Paul G., 1960- |t Design of experiments with MINITAB |z 0873896378 |w (DLC) 2004020013 |w (OCoLC)56413998 |
| 856 | 4 | 0 | |u https://proxy.k.utb.cz/login?url=https://app.knovel.com/hotlink/toc/id:kpDEMINIT1/design-of-experiments?kpromoter=marc |y Full text |
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