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Experimental statistics for agriculture and horticulture / Clive R. Ireland.

By: Ireland, Clive R.
Material type: materialTypeLabelBookSeries: Modular texts: Publisher: Wallingford, Oxfordshire, UK ; Cambridge, MA : CABI, c2010Description: xvi, 360 p. : ill. ; 25 cm.ISBN: 9781845935375 (pbk. : alk. paper); 1845935373 (pbk. : alk. paper).Subject(s): Agriculture -- Experimentation | Agriculture -- Research | Horticulture -- Research -- Statistical methodsDDC classification: 630.727
Contents:
An introduction to research by experimentation -- Descriptive statistics -- Data distributions and their use -- Populations, samples and sample reliability -- Inferential statistics and hypothesis testing -- Single-sample and two-sample parametric tests -- Analysis of multiple-example experiments -- Analysis of multiple-factorial experiments -- Design and analysis of more complex factorial experiments -- Non-parametric sample comparison tests -- Correlation analysis -- Inspecting relationships by simple linear regression analysis -- Multiple regression and non-linear regression analysis -- Analysis of frequency data -- Performing statistical analyses using computer packages and presenting results.
Holdings
Item type Current library Call number Copy number Status Barcode
General lending MTU Bishopstown Library Lending 630.727 (Browse shelf(Opens below)) 1 Available 00161042
General lending MTU Bishopstown Library Lending 630.727 (Browse shelf(Opens below)) 1 Available 00161041
Total holds: 0

Enhanced descriptions from Syndetics:

Providing practical training supported by a sound theoretical basis, this textbook introduces students to the principles of investigation by experiment and the role of statistics in analysis. It draws on the author's extensive teaching experience and is illustrated with fully worked contextualized examples throughout, helping the reader to correctly design their own experiments and identify the most appropriate technique for analysis. Subjects covered include sampling and determining sample reliability, hypothesis testing, relationships between variables, the role and use of computer packages such as Genstat, and more complex experimental designs such as randomized blocks and split plots.

Includes bibliographical references (page 351) and index.

An introduction to research by experimentation -- Descriptive statistics -- Data distributions and their use -- Populations, samples and sample reliability -- Inferential statistics and hypothesis testing -- Single-sample and two-sample parametric tests -- Analysis of multiple-example experiments -- Analysis of multiple-factorial experiments -- Design and analysis of more complex factorial experiments -- Non-parametric sample comparison tests -- Correlation analysis -- Inspecting relationships by simple linear regression analysis -- Multiple regression and non-linear regression analysis -- Analysis of frequency data -- Performing statistical analyses using computer packages and presenting results.

CIT Module MATH 6052 - Supplementary reading.

CIT Library INTR 8015 - Core reading.

Table of contents provided by Syndetics

  • List of Examples
  • Preface
  • Acknowledgements
  • 1 Introduction to Research by Experimentation
  • 2 Descriptive Statistics
  • 3 Data Distributions and Their Use
  • 4 Populations, Samples and Sample Reliability
  • 5 Inferential Statistics and Hypothesis Testing
  • 6 Single-Sample and Two-Sample Parametric Tests
  • 7 Analysis of Multi-sample Experiments
  • 8 Analysis of Multi-factorial Experiments
  • 9 Design and Analysis of More Complex Factorial Experiments
  • 10 Non-Parametric Sample Comparison Tests
  • 11 Correlation Analysis
  • 12 Inspecting Relationships by Simple Linear Regression Analysis
  • 13 Multiple Regression and Non-Linear Regression Analysis
  • 14 Analysis of Frequency Data
  • 15 Performing Statistical Analyses Using Computer Packages and Presenting Results
  • Appendix: Statistical Tables
  • References

Reviews provided by Syndetics

CHOICE Review

Understanding the meaning of statistical terms, concepts, and procedures is a challenge to individuals who are statistically naive. Applying statistical procedures correctly to data and formulating effective experimental designs are not easy to do, especially when the study takes place in a natural habitat or agricultural setting where highly variable data are commonly gathered. The majority of statistical textbooks do not help students overcome this challenge because the narrative emphasizes the wrong topics (probability theory and mathematical proofs) and glosses over application and interpretation of statistics. Following the format of a limited number of truly applied statistics textbooks, this book reverses these tendencies. Short on theory and long on application and explication, it serves as a how-to manual. Ireland (Writtle College, UK) logically structures the narrative, minimizes mathematics, uses only essential technical terms, and provides an explanation as to what the results of statistical procedures can and cannot illustrate. The strengths of this book are the uncomplicated explanations about and visual demonstrations of statistical procedures and concepts. Its limited range and depth of topics restrict its utility to untrained students. Summing Up: Recommended. Upper-division undergraduates and graduate students. S. R. Fegley University of North Carolina at Chapel Hill