Statistical control by monitoring and feedback adjustment [[electronic resource] /] / George E.P. Box, Alberto Luceño, Maria del Carmen Paniagua-Quiñones |
Autore | Box George E. P |
Edizione | [2nd ed.] |
Pubbl/distr/stampa | Hoboken, N.J., : John Wiley & Sons, 2009 |
Descrizione fisica | 1 online resource (358 p.) |
Disciplina |
629.8/3
629.83 |
Altri autori (Persone) |
LuceñoAlberto
Paniagua-QuiñonesMaría del Carmen |
Collana | Wiley series in probability and statistics |
Soggetto topico |
Feedback control systems
Process control - Statistical methods |
Soggetto genere / forma | Electronic books. |
ISBN |
1-283-27393-4
9786613273932 1-118-16453-9 1-118-16446-6 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Statistical Control by Monitoring and Adjustment, Second Edition; Contents; Preface; 1 Introduction and Revision of Some Statistical Ideas; 1.1 Necessity for Process Control; 1.2 SPC and EPC; 1.3 Process Monitoring Without a Model; 1.4 Detecting a Signal in Noise; 1.5 Measurement Data; 1.6 Two Important Characteristics of a Probability Distribution; 1.7 Normal Distribution; 1.8 Normal Distribution Defined by μ and σ; 1.9 Probabilities Associated with Normal Distribution; 1.10 Estimating Mean and Standard Deviation from Data; 1.11 Combining Estimates of σ2
1.12 Data on Frequencies (Events): Poisson Distribution1.13 Normal Approximation to Poisson Distribution; 1.14 Data on Proportion Defective: Binomial Distribution; 1.15 Normal Approximation to Binomial Distribution; Appendix 1A: Central Limit Effect; Problems; 2 Standard Control Charts Under Ideal Conditions As a First Approximation; 2.1 Control Charts for Process Monitoring; 2.2 Control Chart for Measurement (Variables) Data; 2.3 Shewhart Charts for Sample Average and Range; 2.4 Shewhart Chart for Sample Range; 2.5 Process Monitoring With Control Charts for Frequencies 2.6 Data on Frequencies (Counts): Poisson Distribution2.7 Common Causes and Special Causes; 2.8 For What Kinds of Data Has the c Chart Been Used?; 2.9 Quality Control Charts for Proportions: p Chart; 2.10 EWMA Chart; 2.11 Process Monitoring Using Cumulative Sums; 2.12 Specification Limits, Target Accuracy, and Process Capability; 2.13 How Successful Process Monitoring can Improve Quality; Problems; 3 What Can Go Wrong and What Can We Do About It?; 3.1 Introduction; 3.2 Measurement Charts; 3.3 Need for Time Series Models; 3.4 Types of Variation; 3.5 Nonstationary Noise 3.6 Values for constants3.7 Frequencies and Proportions; 3.8 Illustration; 3.9 Robustness of EWMA; Appendix 3A: Alternative Forms of Relationships for EWMAs; Questions; 4 Introduction to Forecasting and Process Dynamics; 4.1 Forecasting with an EWMA; 4.2 Forecasting Sales of Dingles; 4.3 Pete's Rule; 4.4 Effect of Changing Discount Factor; 4.5 Estimating Best Discount Factor; 4.6 Standard Deviation of Forecast Errors and Probability Limits for Forecasts; 4.7 What to Do If You Do Not Have Enough Data to Estimate θ; 4.8 Introduction to Process Dynamics and Transfer Function 4.9 Dynamic Systems and Transfer Funtions4.10 Difference Equations to Represent Dynamic Relations; 4.11 Representing Dynamics of Industrial Process; 4.12 Transfer Function Models Using Difference Equations; 4.13 Stable and Unstable Systems; Problems; 5 Nonstationary Time Series Models for Process Disturbances; 5.1 Reprise; 5.2 Stationary Time Series Model in Which Successive Values Are Correlated; 5.3 Major Effects of Statistical Dependence: Illustration; 5.4 Random Walk; 5.5 How to Test a Forecasting Method; 5.6 Qualification of EWMA As a Forecast 5.7 Understanding Time Series Behavior with Variogram |
Record Nr. | UNINA-9910139597903321 |
Box George E. P
![]() |
||
Hoboken, N.J., : John Wiley & Sons, 2009 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
Statistical control by monitoring and feedback adjustment [[electronic resource] /] / George E.P. Box, Alberto Luceño, Maria del Carmen Paniagua-Quiñones |
Autore | Box George E. P |
Edizione | [2nd ed.] |
Pubbl/distr/stampa | Hoboken, N.J., : John Wiley & Sons, 2009 |
Descrizione fisica | 1 online resource (358 p.) |
Disciplina |
629.8/3
629.83 |
Altri autori (Persone) |
LuceñoAlberto
Paniagua-QuiñonesMaría del Carmen |
Collana | Wiley series in probability and statistics |
Soggetto topico |
Feedback control systems
Process control - Statistical methods |
ISBN |
1-283-27393-4
9786613273932 1-118-16453-9 1-118-16446-6 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Statistical Control by Monitoring and Adjustment, Second Edition; Contents; Preface; 1 Introduction and Revision of Some Statistical Ideas; 1.1 Necessity for Process Control; 1.2 SPC and EPC; 1.3 Process Monitoring Without a Model; 1.4 Detecting a Signal in Noise; 1.5 Measurement Data; 1.6 Two Important Characteristics of a Probability Distribution; 1.7 Normal Distribution; 1.8 Normal Distribution Defined by μ and σ; 1.9 Probabilities Associated with Normal Distribution; 1.10 Estimating Mean and Standard Deviation from Data; 1.11 Combining Estimates of σ2
1.12 Data on Frequencies (Events): Poisson Distribution1.13 Normal Approximation to Poisson Distribution; 1.14 Data on Proportion Defective: Binomial Distribution; 1.15 Normal Approximation to Binomial Distribution; Appendix 1A: Central Limit Effect; Problems; 2 Standard Control Charts Under Ideal Conditions As a First Approximation; 2.1 Control Charts for Process Monitoring; 2.2 Control Chart for Measurement (Variables) Data; 2.3 Shewhart Charts for Sample Average and Range; 2.4 Shewhart Chart for Sample Range; 2.5 Process Monitoring With Control Charts for Frequencies 2.6 Data on Frequencies (Counts): Poisson Distribution2.7 Common Causes and Special Causes; 2.8 For What Kinds of Data Has the c Chart Been Used?; 2.9 Quality Control Charts for Proportions: p Chart; 2.10 EWMA Chart; 2.11 Process Monitoring Using Cumulative Sums; 2.12 Specification Limits, Target Accuracy, and Process Capability; 2.13 How Successful Process Monitoring can Improve Quality; Problems; 3 What Can Go Wrong and What Can We Do About It?; 3.1 Introduction; 3.2 Measurement Charts; 3.3 Need for Time Series Models; 3.4 Types of Variation; 3.5 Nonstationary Noise 3.6 Values for constants3.7 Frequencies and Proportions; 3.8 Illustration; 3.9 Robustness of EWMA; Appendix 3A: Alternative Forms of Relationships for EWMAs; Questions; 4 Introduction to Forecasting and Process Dynamics; 4.1 Forecasting with an EWMA; 4.2 Forecasting Sales of Dingles; 4.3 Pete's Rule; 4.4 Effect of Changing Discount Factor; 4.5 Estimating Best Discount Factor; 4.6 Standard Deviation of Forecast Errors and Probability Limits for Forecasts; 4.7 What to Do If You Do Not Have Enough Data to Estimate θ; 4.8 Introduction to Process Dynamics and Transfer Function 4.9 Dynamic Systems and Transfer Funtions4.10 Difference Equations to Represent Dynamic Relations; 4.11 Representing Dynamics of Industrial Process; 4.12 Transfer Function Models Using Difference Equations; 4.13 Stable and Unstable Systems; Problems; 5 Nonstationary Time Series Models for Process Disturbances; 5.1 Reprise; 5.2 Stationary Time Series Model in Which Successive Values Are Correlated; 5.3 Major Effects of Statistical Dependence: Illustration; 5.4 Random Walk; 5.5 How to Test a Forecasting Method; 5.6 Qualification of EWMA As a Forecast 5.7 Understanding Time Series Behavior with Variogram |
Record Nr. | UNINA-9910831048103321 |
Box George E. P
![]() |
||
Hoboken, N.J., : John Wiley & Sons, 2009 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
Statistical control by monitoring and feedback adjustment / / George E.P. Box, Alberto Luceno, Maria del Carmen Paniagua-Quinones |
Autore | Box George E. P |
Edizione | [2nd ed.] |
Pubbl/distr/stampa | Hoboken, N.J., : John Wiley & Sons, 2009 |
Descrizione fisica | 1 online resource (358 p.) |
Disciplina | 629.8/3 |
Altri autori (Persone) |
LucenoAlberto
Paniagua-QuinonesMaria del Carmen |
Collana | Wiley series in probability and statistics |
Soggetto topico |
Feedback control systems
Process control - Statistical methods |
ISBN |
1-283-27393-4
9786613273932 1-118-16453-9 1-118-16446-6 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Statistical Control by Monitoring and Adjustment, Second Edition; Contents; Preface; 1 Introduction and Revision of Some Statistical Ideas; 1.1 Necessity for Process Control; 1.2 SPC and EPC; 1.3 Process Monitoring Without a Model; 1.4 Detecting a Signal in Noise; 1.5 Measurement Data; 1.6 Two Important Characteristics of a Probability Distribution; 1.7 Normal Distribution; 1.8 Normal Distribution Defined by μ and σ; 1.9 Probabilities Associated with Normal Distribution; 1.10 Estimating Mean and Standard Deviation from Data; 1.11 Combining Estimates of σ2
1.12 Data on Frequencies (Events): Poisson Distribution1.13 Normal Approximation to Poisson Distribution; 1.14 Data on Proportion Defective: Binomial Distribution; 1.15 Normal Approximation to Binomial Distribution; Appendix 1A: Central Limit Effect; Problems; 2 Standard Control Charts Under Ideal Conditions As a First Approximation; 2.1 Control Charts for Process Monitoring; 2.2 Control Chart for Measurement (Variables) Data; 2.3 Shewhart Charts for Sample Average and Range; 2.4 Shewhart Chart for Sample Range; 2.5 Process Monitoring With Control Charts for Frequencies 2.6 Data on Frequencies (Counts): Poisson Distribution2.7 Common Causes and Special Causes; 2.8 For What Kinds of Data Has the c Chart Been Used?; 2.9 Quality Control Charts for Proportions: p Chart; 2.10 EWMA Chart; 2.11 Process Monitoring Using Cumulative Sums; 2.12 Specification Limits, Target Accuracy, and Process Capability; 2.13 How Successful Process Monitoring can Improve Quality; Problems; 3 What Can Go Wrong and What Can We Do About It?; 3.1 Introduction; 3.2 Measurement Charts; 3.3 Need for Time Series Models; 3.4 Types of Variation; 3.5 Nonstationary Noise 3.6 Values for constants3.7 Frequencies and Proportions; 3.8 Illustration; 3.9 Robustness of EWMA; Appendix 3A: Alternative Forms of Relationships for EWMAs; Questions; 4 Introduction to Forecasting and Process Dynamics; 4.1 Forecasting with an EWMA; 4.2 Forecasting Sales of Dingles; 4.3 Pete's Rule; 4.4 Effect of Changing Discount Factor; 4.5 Estimating Best Discount Factor; 4.6 Standard Deviation of Forecast Errors and Probability Limits for Forecasts; 4.7 What to Do If You Do Not Have Enough Data to Estimate θ; 4.8 Introduction to Process Dynamics and Transfer Function 4.9 Dynamic Systems and Transfer Funtions4.10 Difference Equations to Represent Dynamic Relations; 4.11 Representing Dynamics of Industrial Process; 4.12 Transfer Function Models Using Difference Equations; 4.13 Stable and Unstable Systems; Problems; 5 Nonstationary Time Series Models for Process Disturbances; 5.1 Reprise; 5.2 Stationary Time Series Model in Which Successive Values Are Correlated; 5.3 Major Effects of Statistical Dependence: Illustration; 5.4 Random Walk; 5.5 How to Test a Forecasting Method; 5.6 Qualification of EWMA As a Forecast 5.7 Understanding Time Series Behavior with Variogram |
Record Nr. | UNINA-9910877822503321 |
Box George E. P
![]() |
||
Hoboken, N.J., : John Wiley & Sons, 2009 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
Statistical methods for quality improvement / / Thomas P. Ryan |
Autore | Ryan Thomas P. <1945-> |
Edizione | [3rd ed.] |
Pubbl/distr/stampa | Hoboken, N.J., : Wiley, c2011 |
Descrizione fisica | 1 online resource (702 p.) |
Disciplina | 658.5/62 |
Collana | Wiley series in probability and statistics |
Soggetto topico |
Quality control - Statistical methods
Process control - Statistical methods |
ISBN |
1-283-28267-4
9786613282675 1-118-05810-0 1-118-05811-9 1-118-05809-7 |
Classificazione | MAT029000 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Statistical Methods forQuality Improvement; Contents; Preface; Preface to the Second Edition; Preface to the First Edition; PART I FUNDAMENTAL QUALITY IMPROVEMENT AND STATISTICAL CONCEPTS; 1 Introduction; 1.1 Quality and Productivity; 1.2 Quality Costs (or Does It?); 1.3 The Need for Statistical Methods; 1.4 Early Use of Statistical Methods for Improving Quality; 1.5 Influential Quality Experts; 1.6 Summary; References; 2 Basic Tools for Improving Quality; 2.1 Histogram; 2.2 Pareto Charts; 2.3 Scatter Plots; 2.3.1 Variations of Scatter Plots; 2.4 Control Chart; 2.5 Check Sheet
2.6 Cause-and-Effect Diagram2.7 Defect Concentration Diagram; 2.8 The Seven Newer Tools; 2.8.1 Affinity Diagram; 2.8.2 Interrelationship Digraph; 2.8.3 Tree Diagram; 2.8.4 Prioritization Matrix; 2.8.5 Matrix Diagram; 2.8.6 Process Decision Program Chart; 2.8.7 Activity Network Diagram; 2.9 Software; 2.10 Summary; References; Exercises; 3 Basic Concepts in Statistics and Probability; 3.1 Probability; 3.2 Sample Versus Population; 3.3 Location; 3.4 Variation; 3.5 Discrete Distributions; 3.5.1 Binomial Distribution; 3.5.2 Beta-Binomial Distribution; 3.5.3 Poisson Distribution 3.5.4 Geometric Distribution3.5.5 Negative Binomial Distribution; 3.5.6 Hypergeometric Distribution; 3.6 Continuous Distributions; 3.6.1 Normal Distribution; 3.6.2 t Distribution; 3.6.3 Exponential Distribution; 3.6.4 Lognormal Distribution; 3.6.5 Weibull Distribution; 3.6.6 Extreme Value Distribution; 3.6.7 Gamma Distribution; 3.6.8 Chi-Square Distribution; 3.6.9 Truncated Normal Distribution; 3.6.10 Bivariate and Multivariate Normal Distributions; 3.6.11 F Distribution; 3.6.12 Beta Distribution; 3.6.13 Uniform Distribution; 3.7 Choice of Statistical Distribution; 3.8 Statistical Inference 3.8.1 Central Limit Theorem3.8.2 Point Estimation; 3.8.2.1 Maximum Likelihood Estimation; 3.8.3 Confidence Intervals; 3.8.4 Tolerance Intervals; 3.8.5 Hypothesis Tests; 3.8.5.1 Probability Plots; 3.8.5.2 Likelihood Ratio Tests; 3.8.6 Bonferroni Intervals; 3.9 Enumerative Studies Versus Analytic Studies; References; Exercises; PARTII CONTROL CHARTS AND PROCESS CAPABILITY; 4 Control Charts for Measurements With Subgrouping (for One Variable); 4.1 Basic Control Chart Principles; 4.2 Real-Time Control Charting Versus Analysis of Past Data 4.3 Control Charts: When to Use, Where to Use, How Many to Use4.4 Benefits from the Use of Control Charts; 4.5 Rational Subgroups; 4.6 Basic Statistical Aspects of Control Charts; 4.7 Illustrative Example; 4.7.1 R-Chart; 4.7.2 R-Chart with Probability Limits; 4.7.3 S-Chart; 4.7.4 S-Chart with Probability Limits; 4.7.5 S2-Chart; 4.7.6 X-Chart; 4.7.7 Recomputing Control Limits; 4.7.8 Applying Control Limits to Future Production; 4.7.9 Combining an X- and an S-Chart; 4.7.10 Standards for Control Charts; 4.7.11 Deleting Points; 4.7.12 Target Values; 4.8 Illustrative Example with Real Data 4.9 Determining the Point of a Parameter Change |
Record Nr. | UNINA-9910133222103321 |
Ryan Thomas P. <1945->
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Hoboken, N.J., : Wiley, c2011 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
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Statistical methods for quality improvement [e-book] / Thomas P. Ryan |
Autore | Ryan, Thomas P. |
Edizione | [3rd ed.] |
Pubbl/distr/stampa | Hoboken, N.J. : Wiley, c2011 |
Descrizione fisica | 1 online resource (666 p.) : illustrations |
Disciplina | 658.5/62 |
Collana | Wiley series in probability and statistics |
Soggetto topico |
Quality control - Statistical methods
Process control - Statistical methods |
ISBN | 9781118058114 |
Classificazione | LC TS156 |
Formato | Software ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNISALENTO-991003937299707536 |
Ryan, Thomas P.
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Hoboken, N.J. : Wiley, c2011 | ||
![]() | ||
Lo trovi qui: Univ. del Salento | ||
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Statistical methods for six sigma [[electronic resource] ] : in R&D and manufacturing / / Anand M. Joglekar |
Autore | Joglekar Anand M |
Pubbl/distr/stampa | Hoboken, NJ, : Wiley-Interscience, 2003 |
Descrizione fisica | 1 online resource (339 p.) |
Disciplina |
519.5
551.51/5 658.5/62 |
Soggetto topico |
Quality control - Statistical methods
Process control - Statistical methods |
Soggetto genere / forma | Electronic books. |
ISBN |
1-280-36769-5
9786610367696 0-470-24804-1 0-471-46537-2 0-471-72121-2 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Statistical Methods for Six Sigma; Contents; Preface; 1 Introduction; 2 Basic Statistics; 2.1 Descriptive Statistics; 2.1.1 Measures of Central Tendency; 2.1.2 Measures of Variability; 2.1.3 Histogram; 2.2 Statistical Distributions; 2.2.1 Normal Distribution; 2.2.2 Binomial Distribution; 2.2.3 Poisson Distribution; 2.3 Confidence Intervals; 2.3.1 Confidence Interval for m; 2.3.2 Confidence Interval for s; 2.3.3 Confidence Interval for p and l; 2.4 Sample Size; 2.4.1 Sample Size to Estimate m; 2.4.2 Sample Size to Estimate s; 2.4.3 Sample Size to Estimate p and l; 2.5 Tolerance Intervals
2.6 Normality, Independence, and Homoscedasticity2.6.1 Normality; 2.6.2 Independence; 2.6.3 Homoscedasticity; 3 Comparative Experiments and Regression Analysis; 3.1 Hypothesis Testing Framework; 3.2 Comparing Single Population; 3.2.1 Comparing Mean (Variance Known); 3.2.2 Comparing Mean (Variance Unknown); 3.2.3 Comparing Standard Deviation; 3.2.4 Comparing Proportion; 3.3 Comparing Two Populations; 3.3.1 Comparing Two Means (Variance Known); 3.3.2 Comparing Two Means (Variance Unknown but Equal); 3.3.3 Comparing Two Means (Variance Unknown and Unequal) 3.3.4 Comparing Two Means (Paired t-test)3.3.5 Comparing Two Standard Deviations; 3.3.6 Comparing Two Proportions; 3.4 Comparing Multiple Populations; 3.4.1 Completely Randomized Design; 3.4.2 Randomized Block Design; 3.4.3 Multiple Comparison Procedures; 3.4.4 Comparing Multiple Standard Deviations; 3.5 Correlation; 3.5.1 Scatter Diagram; 3.5.2 Correlation Coefficient; 3.6 Regression Analysis; 3.6.1 Fitting Equations to Data; 3.6.2 Accelerated Stability Tests; 4 Control Charts; 4.1 Role of Control Charts; 4.2 Logic of Control Limits; 4.3 Variable Control Charts 4.3.1 Average and Range Charts4.3.2 Average and Standard Deviation Charts; 4.3.3 Individual and Moving Range Charts; 4.4 Attribute Control Charts; 4.4.1 Fraction Defective (p) Chart; 4.4.2 Defects per Product (u) Chart; 4.5 Interpreting Control Charts; 4.5.1 Tests for the Chart of Averages; 4.5.2 Tests for Other Charts; 4.6 Key Success Factors; 5 Process Capability; 5.1 Capability and Performance Indices; 5.1.1 C(p) Index; 5.1.2 C(pk) Index; 5.1.3 P(p) Index; 5.1.4 P(pk) Index; 5.1.5 Relationships between C(p), C(pk), P(p), and P(pk); 5.2 Estimating Capability and Performance Indices 5.2.1 Point Estimates for Capability and Performance Indices5.2.2 Confidence Intervals for Capability and Performance Indices; 5.2.3 Connection with Tolerance Intervals; 5.3 Six-Sigma Goal; 5.4 Planning for Improvement; 6 Other Useful Charts; 6.1 Risk-based Control Charts; 6.1.1 Control Limits, Subgroup Size, and Risks; 6.1.2 Risk-Based X Chart; 6.1.3 Risk-Based Attribute Charts; 6.2 Modified Control Limit X Chart; 6.2.1 Chart Design; 6.2.2 Required Minimum C(pk); 6.3 Moving Average Control Chart; 6.4 Short-Run Control Charts; 6.4.1 Short-Run Individual and Moving Range Charts 6.4.2 Short-Run Average and Range Charts |
Record Nr. | UNINA-9910143182603321 |
Joglekar Anand M
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Hoboken, NJ, : Wiley-Interscience, 2003 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
Statistical methods for six sigma [[electronic resource] ] : in R&D and manufacturing / / Anand M. Joglekar |
Autore | Joglekar Anand M |
Pubbl/distr/stampa | Hoboken, NJ, : Wiley-Interscience, 2003 |
Descrizione fisica | 1 online resource (339 p.) |
Disciplina |
519.5
551.51/5 658.5/62 |
Soggetto topico |
Quality control - Statistical methods
Process control - Statistical methods |
ISBN |
1-280-36769-5
9786610367696 0-470-24804-1 0-471-46537-2 0-471-72121-2 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Statistical Methods for Six Sigma; Contents; Preface; 1 Introduction; 2 Basic Statistics; 2.1 Descriptive Statistics; 2.1.1 Measures of Central Tendency; 2.1.2 Measures of Variability; 2.1.3 Histogram; 2.2 Statistical Distributions; 2.2.1 Normal Distribution; 2.2.2 Binomial Distribution; 2.2.3 Poisson Distribution; 2.3 Confidence Intervals; 2.3.1 Confidence Interval for m; 2.3.2 Confidence Interval for s; 2.3.3 Confidence Interval for p and l; 2.4 Sample Size; 2.4.1 Sample Size to Estimate m; 2.4.2 Sample Size to Estimate s; 2.4.3 Sample Size to Estimate p and l; 2.5 Tolerance Intervals
2.6 Normality, Independence, and Homoscedasticity2.6.1 Normality; 2.6.2 Independence; 2.6.3 Homoscedasticity; 3 Comparative Experiments and Regression Analysis; 3.1 Hypothesis Testing Framework; 3.2 Comparing Single Population; 3.2.1 Comparing Mean (Variance Known); 3.2.2 Comparing Mean (Variance Unknown); 3.2.3 Comparing Standard Deviation; 3.2.4 Comparing Proportion; 3.3 Comparing Two Populations; 3.3.1 Comparing Two Means (Variance Known); 3.3.2 Comparing Two Means (Variance Unknown but Equal); 3.3.3 Comparing Two Means (Variance Unknown and Unequal) 3.3.4 Comparing Two Means (Paired t-test)3.3.5 Comparing Two Standard Deviations; 3.3.6 Comparing Two Proportions; 3.4 Comparing Multiple Populations; 3.4.1 Completely Randomized Design; 3.4.2 Randomized Block Design; 3.4.3 Multiple Comparison Procedures; 3.4.4 Comparing Multiple Standard Deviations; 3.5 Correlation; 3.5.1 Scatter Diagram; 3.5.2 Correlation Coefficient; 3.6 Regression Analysis; 3.6.1 Fitting Equations to Data; 3.6.2 Accelerated Stability Tests; 4 Control Charts; 4.1 Role of Control Charts; 4.2 Logic of Control Limits; 4.3 Variable Control Charts 4.3.1 Average and Range Charts4.3.2 Average and Standard Deviation Charts; 4.3.3 Individual and Moving Range Charts; 4.4 Attribute Control Charts; 4.4.1 Fraction Defective (p) Chart; 4.4.2 Defects per Product (u) Chart; 4.5 Interpreting Control Charts; 4.5.1 Tests for the Chart of Averages; 4.5.2 Tests for Other Charts; 4.6 Key Success Factors; 5 Process Capability; 5.1 Capability and Performance Indices; 5.1.1 C(p) Index; 5.1.2 C(pk) Index; 5.1.3 P(p) Index; 5.1.4 P(pk) Index; 5.1.5 Relationships between C(p), C(pk), P(p), and P(pk); 5.2 Estimating Capability and Performance Indices 5.2.1 Point Estimates for Capability and Performance Indices5.2.2 Confidence Intervals for Capability and Performance Indices; 5.2.3 Connection with Tolerance Intervals; 5.3 Six-Sigma Goal; 5.4 Planning for Improvement; 6 Other Useful Charts; 6.1 Risk-based Control Charts; 6.1.1 Control Limits, Subgroup Size, and Risks; 6.1.2 Risk-Based X Chart; 6.1.3 Risk-Based Attribute Charts; 6.2 Modified Control Limit X Chart; 6.2.1 Chart Design; 6.2.2 Required Minimum C(pk); 6.3 Moving Average Control Chart; 6.4 Short-Run Control Charts; 6.4.1 Short-Run Individual and Moving Range Charts 6.4.2 Short-Run Average and Range Charts |
Record Nr. | UNINA-9910829827503321 |
Joglekar Anand M
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Hoboken, NJ, : Wiley-Interscience, 2003 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
Statistical methods for six sigma : in R&D and manufacturing / / Anand M. Joglekar |
Autore | Joglekar Anand M |
Pubbl/distr/stampa | Hoboken, NJ, : Wiley-Interscience, 2003 |
Descrizione fisica | 1 online resource (339 p.) |
Disciplina | 658.5/62 |
Soggetto topico |
Quality control - Statistical methods
Process control - Statistical methods |
ISBN |
1-280-36769-5
9786610367696 0-470-24804-1 0-471-46537-2 0-471-72121-2 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Statistical Methods for Six Sigma; Contents; Preface; 1 Introduction; 2 Basic Statistics; 2.1 Descriptive Statistics; 2.1.1 Measures of Central Tendency; 2.1.2 Measures of Variability; 2.1.3 Histogram; 2.2 Statistical Distributions; 2.2.1 Normal Distribution; 2.2.2 Binomial Distribution; 2.2.3 Poisson Distribution; 2.3 Confidence Intervals; 2.3.1 Confidence Interval for m; 2.3.2 Confidence Interval for s; 2.3.3 Confidence Interval for p and l; 2.4 Sample Size; 2.4.1 Sample Size to Estimate m; 2.4.2 Sample Size to Estimate s; 2.4.3 Sample Size to Estimate p and l; 2.5 Tolerance Intervals
2.6 Normality, Independence, and Homoscedasticity2.6.1 Normality; 2.6.2 Independence; 2.6.3 Homoscedasticity; 3 Comparative Experiments and Regression Analysis; 3.1 Hypothesis Testing Framework; 3.2 Comparing Single Population; 3.2.1 Comparing Mean (Variance Known); 3.2.2 Comparing Mean (Variance Unknown); 3.2.3 Comparing Standard Deviation; 3.2.4 Comparing Proportion; 3.3 Comparing Two Populations; 3.3.1 Comparing Two Means (Variance Known); 3.3.2 Comparing Two Means (Variance Unknown but Equal); 3.3.3 Comparing Two Means (Variance Unknown and Unequal) 3.3.4 Comparing Two Means (Paired t-test)3.3.5 Comparing Two Standard Deviations; 3.3.6 Comparing Two Proportions; 3.4 Comparing Multiple Populations; 3.4.1 Completely Randomized Design; 3.4.2 Randomized Block Design; 3.4.3 Multiple Comparison Procedures; 3.4.4 Comparing Multiple Standard Deviations; 3.5 Correlation; 3.5.1 Scatter Diagram; 3.5.2 Correlation Coefficient; 3.6 Regression Analysis; 3.6.1 Fitting Equations to Data; 3.6.2 Accelerated Stability Tests; 4 Control Charts; 4.1 Role of Control Charts; 4.2 Logic of Control Limits; 4.3 Variable Control Charts 4.3.1 Average and Range Charts4.3.2 Average and Standard Deviation Charts; 4.3.3 Individual and Moving Range Charts; 4.4 Attribute Control Charts; 4.4.1 Fraction Defective (p) Chart; 4.4.2 Defects per Product (u) Chart; 4.5 Interpreting Control Charts; 4.5.1 Tests for the Chart of Averages; 4.5.2 Tests for Other Charts; 4.6 Key Success Factors; 5 Process Capability; 5.1 Capability and Performance Indices; 5.1.1 C(p) Index; 5.1.2 C(pk) Index; 5.1.3 P(p) Index; 5.1.4 P(pk) Index; 5.1.5 Relationships between C(p), C(pk), P(p), and P(pk); 5.2 Estimating Capability and Performance Indices 5.2.1 Point Estimates for Capability and Performance Indices5.2.2 Confidence Intervals for Capability and Performance Indices; 5.2.3 Connection with Tolerance Intervals; 5.3 Six-Sigma Goal; 5.4 Planning for Improvement; 6 Other Useful Charts; 6.1 Risk-based Control Charts; 6.1.1 Control Limits, Subgroup Size, and Risks; 6.1.2 Risk-Based X Chart; 6.1.3 Risk-Based Attribute Charts; 6.2 Modified Control Limit X Chart; 6.2.1 Chart Design; 6.2.2 Required Minimum C(pk); 6.3 Moving Average Control Chart; 6.4 Short-Run Control Charts; 6.4.1 Short-Run Individual and Moving Range Charts 6.4.2 Short-Run Average and Range Charts |
Record Nr. | UNINA-9910876662403321 |
Joglekar Anand M
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Hoboken, NJ, : Wiley-Interscience, 2003 | ||
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Lo trovi qui: Univ. Federico II | ||
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Statistical process control [e-book] / John S. Oakland |
Autore | Oakland, John S. |
Edizione | [5th ed.] |
Pubbl/distr/stampa | Oxford ; Boston : Butterworth-Heinemann, 2003 |
Descrizione fisica | xiii, 445 p. : ill. ; 24 cm |
Disciplina | 658.562015195 |
Altri autori (Enti) | Elsevier Science Publishers |
Soggetto topico |
Process control - Statistical methods
Quality control - Statistical methods |
Soggetto genere / forma | Electronic books |
Formato | Risorse elettroniche ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNISALENTO-991003225399707536 |
Oakland, John S.
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Oxford ; Boston : Butterworth-Heinemann, 2003 | ||
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Lo trovi qui: Univ. del Salento | ||
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Statistical process control for managers / / Victor E. Sower |
Autore | Sower Victor E. |
Edizione | [Second edition.] |
Pubbl/distr/stampa | New York, NY : , : Business Expert Press, , 2017 |
Descrizione fisica | 1 online resource (170 pages) |
Disciplina | 658.562015195 |
Collana | Supply and operations management collection |
Soggetto topico | Process control - Statistical methods |
Soggetto genere / forma | Electronic books. |
ISBN | 1-947098-79-9 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910467357103321 |
Sower Victor E.
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New York, NY : , : Business Expert Press, , 2017 | ||
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Lo trovi qui: Univ. Federico II | ||
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