1978 StatisticsforExperimentersAnInt

• (Box et al., 1978) ⇒ George EP Box, William G Hunter, and J Stuart Hunter. (1978). “Statistics for Experimenters: An Introduction to Design, Data Analysis, and Model Building.” John Wiley & Sons. ISBN:0471093157

Subject Headings: Experimental Error, Experimental Design, Controlled Experiment, Fractional Factorial Design, ANOVA.

Cited By

• http://scholar.google.com/scholar?q=%22Statistics+for+experimenters%3A+an+introduction+to+design%2C+data+analysis%2C+and+model+building%22+1978

Quotes

Table of Contents

Chapter 1. Science and Statistics
Part I. Comparing Two Treatments
Chapter 2. Use of External Reference Distribution to Compare Two Means
Chapter 3. Random Sampling and the Declaration of Independence
Chapter 4. Randomization and Blocking with Paired Comparisons
Chapter 5. Significance Tests and Confidence Intervals for Means, Variances, Proportions and Frequences.
Part II. Comparing More Than Two Treatments.
Chapter 6. Experiments to Compare k Treatment Means
Chapter 7. Randomized Block and Two-Way Factorial Designs
Chapter 8. Designs with More Than One Blocking Variable
Part III. Measuring The Effects of Variables
Chapter 9. Empirical Modeling
Chapter 10. Factorial Designs at Two Levels
Chapter 11. More Applications of Factorial Designs
Chapter 12. Fractional Factorial Designs at Two Levels
Chapter 13. More Applications of Fractional Factorial Designs
Part IV. Building Models and Using Them.
Chapter 14. Simple Modeling with Least Squares (Regression Analysis)
Chapter 15. Response Surface Methods
Chapter 16. Mechanistic Model Building
Chapter 17. Study of Variation
Chapter 18. Modeling Dependence: Times Series

Chapter 1. Science and Statistics

1.1 The Learning Process

Scientific research is a process of guided learning. The object of statistical methods is to make that process as efficient as possible.

Learning is advanced by the iteratin illustrated in Figure 1.1. An initial hypothesis leads by a process of deduction to certain necessary consequences that may be compared with data. When consequences and data fit to agree, the discrepancy can lead, by a process called induction, to modification of the hypothesis.

References

,

	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
1978 StatisticsforExperimentersAnInt	William G Hunter J Stuart Hunter George E. P. Box			Statistics for Experimenters: An Introduction to Design, Data Analysis, and Model Building						1978