Description

Book Synopsis
Progress in engineering and the physical sciences, agriculture and the biological sciences, and to some extent social science, depends on experiments. The design of such experiments is crucial. If they are poorly designed they will be inefficient and may lead to misleading conclusions.

Table of Contents
Preface.

Notation.

Website for data sets.

Sources of data.

1 Guide.

2 Descriptive statistics and plotting.

3 Single sample experiments.

4 Comparison proportions.

5 Comparing two treatments.

6 Comparison of several means.

7 Factorial experiments with factors at two levels.

8 Fractional factorial experiments with factors at two levels.

9 Response surfaces.

10 Hill climbing.

11 Robust design.

12 Hierarchical (nested) designs.

13 Two factors at several levels.

14 Crossed and nested factors, and split-plot designs.

15 Mixture designs.

16 Discrete response.

Post-script.

Authors.

Glossary.

References.

Index.

Design and Analyse Your Experiment Using MINITAB

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    Order before 4pm today for delivery by Wed 24 Jun 2026.

    A Paperback / softback by Tony Greenfield, Andrew V. Metcalfe


      View other formats and editions of Design and Analyse Your Experiment Using MINITAB by Tony Greenfield

      Publisher: John Wiley & Sons Inc
      Publication Date: 23/02/2007
      ISBN13: 9780470711149, 978-0470711149
      ISBN10: 0470711140
      Also in:
      Mathematics

      Description

      Book Synopsis
      Progress in engineering and the physical sciences, agriculture and the biological sciences, and to some extent social science, depends on experiments. The design of such experiments is crucial. If they are poorly designed they will be inefficient and may lead to misleading conclusions.

      Table of Contents
      Preface.

      Notation.

      Website for data sets.

      Sources of data.

      1 Guide.

      2 Descriptive statistics and plotting.

      3 Single sample experiments.

      4 Comparison proportions.

      5 Comparing two treatments.

      6 Comparison of several means.

      7 Factorial experiments with factors at two levels.

      8 Fractional factorial experiments with factors at two levels.

      9 Response surfaces.

      10 Hill climbing.

      11 Robust design.

      12 Hierarchical (nested) designs.

      13 Two factors at several levels.

      14 Crossed and nested factors, and split-plot designs.

      15 Mixture designs.

      16 Discrete response.

      Post-script.

      Authors.

      Glossary.

      References.

      Index.

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