Chapter 1--Fundamental Concepts in the Statistical Planning (Design) of Fatigue Experiments

Chapter 1--Fundamental Concepts in the Statistical Planning (Design) of Fatigue Experiments
Author:
Publisher:
Total Pages: 31
Release: 1975
Genre: Hypothesis
ISBN:

No manual can provide the fatigue investigator with a complete step-by-step detailed procedure which is valid for the statistical planning of experiments whatever the situation. In fact, only certain very simple fatigue test programs fit precisely into the specific formats required for wellestablished planned experiments, such as the completely randomized design (CRD) and the randomized complete block (RCB) design, [1]. Generally these simple fatigue test programs pertain to either elementary comparative tests (for example, comparing the fatigue life of Material A versus Material B), or to quality assurance tests (namely, the generation of certain fatigue data under well-defined test conditions). On the other hand, most (exploratory) research programs involve one or more (sometimes subtle) constraints peculiar to the specific situation, that is, to the given material processing, specimen preparation, test machine, environment, or whatever. Such constraints often preclude elementary statistical analysis of the resulting data and may even present difficulties to a trained statistician, particularly if he is consulted only after the tests have been conducted. But whatever the nature and the complexity of the given fatigue test situation, there are certain design of experiments fundamentals which must appear in the planning and conduct of any competent experimental program. It is the objective of this chapter of the manual to state these fundamentals (presented in italics in the following paragraph) and to illustrate their application in a few example situations. For further specific references to the design of experiments, see Refs 2, 3, and 4.

Fundamental Concepts in the Design of Experiments

Fundamental Concepts in the Design of Experiments
Author: Charles Robert Hicks
Publisher: Holt McDougal
Total Pages: 372
Release: 1973
Genre: Reference
ISBN:

The experiment, the design, and the analysis; Review of statistical inference; Single-factor experiments with no restrictions on randomization; Single-factor experiments - randomized block design; Single-factor experiments - latin and other squares; Factorial experiments; 2n factorial experiments; Qualitative and quantitative factors; 3n factorial experiments; Fixed, random and mixed models; Nested and nested-factorial experiments; Experiments of two or more factors - restrictions on 4randomization; Factorial experiments - split-plot design; Factorial experiment - confounding in blocks; Franctional replication; Miscellaneous topics.

Design and Analysis of Experiments, Volume 1

Design and Analysis of Experiments, Volume 1
Author: Klaus Hinkelmann
Publisher: John Wiley & Sons
Total Pages: 640
Release: 2007-12-04
Genre: Mathematics
ISBN: 0470191740

This user-friendly new edition reflects a modern and accessible approach to experimental design and analysis Design and Analysis of Experiments, Volume 1, Second Edition provides a general introduction to the philosophy, theory, and practice of designing scientific comparative experiments and also details the intricacies that are often encountered throughout the design and analysis processes. With the addition of extensive numerical examples and expanded treatment of key concepts, this book further addresses the needs of practitioners and successfully provides a solid understanding of the relationship between the quality of experimental design and the validity of conclusions. This Second Edition continues to provide the theoretical basis of the principles of experimental design in conjunction with the statistical framework within which to apply the fundamental concepts. The difference between experimental studies and observational studies is addressed, along with a discussion of the various components of experimental design: the error-control design, the treatment design, and the observation design. A series of error-control designs are presented based on fundamental design principles, such as randomization, local control (blocking), the Latin square principle, the split-unit principle, and the notion of factorial treatment structure. This book also emphasizes the practical aspects of designing and analyzing experiments and features: Increased coverage of the practical aspects of designing and analyzing experiments, complete with the steps needed to plan and construct an experiment A case study that explores the various types of interaction between both treatment and blocking factors, and numerical and graphical techniques are provided to analyze and interpret these interactions Discussion of the important distinctions between two types of blocking factors and their role in the process of drawing statistical inferences from an experiment A new chapter devoted entirely to repeated measures, highlighting its relationship to split-plot and split-block designs Numerical examples using SAS® to illustrate the analyses of data from various designs and to construct factorial designs that relate the results to the theoretical derivations Design and Analysis of Experiments, Volume 1, Second Edition is an ideal textbook for first-year graduate courses in experimental design and also serves as a practical, hands-on reference for statisticians and researchers across a wide array of subject areas, including biological sciences, engineering, medicine, pharmacology, psychology, and business.

Planning of Experiments

Planning of Experiments
Author: D. R. Cox
Publisher:
Total Pages: 328
Release: 1958
Genre: Design
ISBN:

Preliminaries. Some Key assumptions. Designs for the reduction of error. Use of supplementary observations to reduce error. Randomization. Basic ideas about factorial experiments. Design of simple factorial experiments. Choice of number of observations. Choice of units, treatments, and observations. More about latin squares. Incomplete nonfactorial designs. Fractional replication and confounding. Cross-over designs. Some special problems.