Industrial statistics : practical methods and guidance for improved performance / Anand M. Joglekar.

Includes bibliographical references and index.

1. Basic statistics - how to reduce long term portfolio risk? -- 1.1. Capital market returns -- 1.2. Sample statistics -- 1.3. Population parameters -- 1.4. Confidence intervals and sample sizes -- 1.5. Correlation -- 1.6. Portfolio optimization -- 1.7. Questions to ask -- 2. Why not to do the usual t-test and what to replace it with? -- 2.1. What is a t-test and what is wrong with it? -- 2.2. Confidence interval is better than a t-test -- 2.3. How much data to collect? -- 2.4. Reducing sample size -- 2.5. Paired comparison -- 2.6. Comparing two standard deviations -- 2.7. Recommended design and analysis procedure -- 2.8. Questions to ask -- 3. Design of experiments - is it not going to cost too much and take too long? -- 3.1. Why design experiments? -- 3.2. Factorial designs -- 3.3. Success factors -- 3.4. Fractional factorial designs -- 3.5. Plackett-Burman designs -- 3.6. Applications -- 3.7. Optimization designs -- 3.8. Questions to ask -- 4. What is the key to designing robust products and processes? -- 4.1. The key to robustness -- 4.2. Robust design method -- 4.3. Signal to noise ratios -- 4.4. Achieving additivity -- 4.5. Implications for R&D -- 4.6. Questions to ask -- 5. Setting specifications - arbitrary or is there a method to it? -- 5.1. Understanding specifications -- 5.2. Empirical approach -- 5.3. Functional approach -- 5.4. Minimum life-cycle cost approach -- 5.5. Questions to ask -- 6. How to design acceptance sampling plans and process validation studies? -- 6.1. Attribute single sample plans -- 6.2. Selecting AQL and RQL -- 6.3. Other acceptance sampling plans -- 6.4. Designing validation studies -- 6.5. Questions to ask -- 7. Managing and improving processes - how to use an at-a-glance display? -- 7.1. Statistical logic of control limits -- 7.2. Selecting subgroup size -- 7.3. Selecting sampling interval -- 7.4. Out of control rules -- 7.5. Process capability and performance indices -- 7.6. At-a-glance display -- 7.7. Questions to ask -- 8. How to find causes of variation by just looking systematically? -- 8.1. Manufacturing application -- 8.2. Variance components analysis -- 8.3. Planning for quality improvement -- 8.4. Structured studies -- 8.5. Questions to ask -- 9. Is my measurement system acceptable - and how to design and improve it? -- 9.1. Acceptance criteria -- 9.2. Designing cost-effective sampling schemes -- 9.3. Designing a robust measurement system -- 9.4. Measurement system validation -- 9.5. Repeatability and Reproducibility (R&R) study -- 9.6. Questions to ask -- 10. How to use theory effectively? -- 10.1. Empirical models -- 10.2. Mechanistic models -- 10.3. Mechanistic model for coal weight CV -- 10.4. Questions to ask -- 11. Questions and Answers -- 11.1. Questions -- 11.2. Answers.

Machine converted from AACR2 source record.