
- 488 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
eBook - ePub
Statistical Methods in Agriculture and Experimental Biology
About this book
The third edition of this popular introductory text maintains the character that won worldwide respect for its predecessors but features a number of enhancements that broaden its scope, increase its utility, and bring the treatment thoroughly up to date. It provides complete coverage of the statistical ideas and methods essential to students in agriculture or experimental biology. In addition to covering fundamental methodology, this treatment also includes more advanced topics that the authors believe help develop an appreciation of the breadth of statistical methodology now available. The emphasis is not on mathematical detail, but on ensuring students understand why and when various methods should be used.
New in the Third Edition:
- A chapter on the two simplest yet most important methods of multivariate analysis
- Increased emphasis on modern computer applications
- Discussions on a wider range of data types and the graphical display of data
- Analysis of mixed cropping experiments and on-farm experiments
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Please note we cannot support devices running on iOS 13 and Android 7 or earlier. Learn more about using the app.
Yes, you can access Statistical Methods in Agriculture and Experimental Biology by Roger Mead in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Cover
- Half Title
- Title Page
- Copyright Page
- Table of Contents
- Preface
- 1 Introduction
- 2 Probability and Distributions
- 3 Estimation and Hypothesis Testing
- 4 A Simple Experiment
- 5 Control of Random Variation by Blocking
- 6 Particular Questions About Treatments
- 7 More on Factorial Treatment Structure
- 8 The Assumptions Behind the Analysis
- 9 Studying Linear Relationships
- 10 More Complex Relationships
- 11 Linear Models
- 12 Nonlinear Models
- 13 The Analysis of Proportions
- 14 Models and Distributions for Frequency Data
- 15 Making and Analyzing Several Experimental Measurements
- 16 Analyzing and Summarizing Many Measurements
- 17 Choosing the Most Appropriate Experimental Design
- 18 Sampling Finite Populations
- References
- Appendix
- Index