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E-grāmata: Design of Experiments for Agriculture and the Natural Sciences

  • Formāts: 456 pages
  • Izdošanas datums: 03-Oct-2018
  • Izdevniecība: Chapman & Hall/CRC
  • ISBN-13: 9781420010640
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Design of Experiments for Agriculture and the Natural SciencesPalielināt
  • Formāts: 456 pages
  • Izdošanas datums: 03-Oct-2018
  • Izdevniecība: Chapman & Hall/CRC
  • ISBN-13: 9781420010640
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Written to meet the needs of both students and applied researchers, Design of Experiments for Agriculture and the Natural Sciences, Second Edition serves as an introductory guide to experimental design and analysis. Like the popular original, this thorough text provides an understanding of the logical underpinnings of design and analysis by selecting and discussing only those carefully chosen designs that offer the greatest utility. However, it improves on the first edition by adhering to a step-by-step process that greatly improves accessibility and understanding. Real problems from different areas of agriculture and science are presented throughout to show how practical issues of design and analysis are best handled.

Completely revised to greatly enhance readability, this new edition includes:





A new chapter on covariance analysis to help readers reduce errors, while enhancing their ability to examine covariances among selected variables Expanded material on multiple regression and variance analysis Additional examples, problems, and case studies A step-by-step Minitab® guide to help with data analysis

Intended for those in the agriculture, environmental, and natural science fields as well as statisticians, this text requires no previous exposure to analysis of variance, although some familiarity with basic statistical fundamentals is assumed. In keeping with the book's practical orientation, numerous workable problems are presented throughout to reinforce the reader's ability to creatively apply the principles and concepts in any given situation.

Recenzijas

" guides readers to think through their problems, to design experiments to answer their questions, to analyze the data accruing from those experiments, and to draw sensible inferences. the exercises at the end of the chapter give readers the opportunity to test their understanding. a handy companion for agronomists and environmental scientists who need to experiment with treatments they can control." -R. Webster, Journal of Environmental Quality, Vol. 36, Issue 1, January-February 2007

"One strength of the text is that there are many actual agricultural and biological examples and data analysis problems. This text would be beneficial to those whose backgrounds are in agriculture and biology, those who would like to see basic computational details, and those who prefer the classical test statistic/critical value approach to hypothesis testing." -Biometrics, December 2006

The Nature of Agricultural Research
1(13)
Fundamental Concepts
1(5)
Research by Practitioners
6(7)
Key Assumptions of Experimental Designs
13(24)
Introduction
13(1)
Assumptions of the Analysis of Variance (ANOVA) and Their Violations
14(5)
Measures to Detect Failures of the Assumptions
19(8)
Data Transformation
27(10)
Designs for Reducing Error
37(14)
Introduction
37(3)
Increasing the Size of the Experiment
37(2)
Refining the Experimental Conditions
39(1)
Reducing Variability in the Experimental Material
40(1)
Approaches to Eliminating Uncontrolled Variations
40(2)
Error Elimination by Several Groupings of Units
42(9)
Latin Square
42(3)
Combined Latin Square
45(2)
Greco-Latin Square
47(4)
Single-Factor Experimental Designs
51(68)
Introduction
51(1)
Complete Block Designs
51(32)
Completely Randomized Design (CRD)
51(13)
Randomized Complete Block (RCB) Design
64(9)
Latin Square Designs
73(10)
Incomplete Block Designs
83(36)
Balanced Lattice Designs
85(9)
Partially Balanced Lattice Designs
94(25)
Two-Factor Experimental Designs
119(40)
Factorial Experiments
119(5)
Main Effects and Interactions in a Two-Factor Experiment
124(4)
Interpretation of Interactions
128(1)
Factorials in Complete Block Designs
129(6)
Split-Plot or Nested Designs
135(9)
Strip-Plot Design
144(15)
Three (or More)-Factor Experimental Designs
159(46)
Introduction
159(2)
Split-Split-Plot Design
161(11)
Strip-Split-Plot Design
172(13)
Factorial Experiments in Fractional Replication
185(20)
Aliases and Defining Contrasts
186(19)
Treatment Means Comparisons
205(34)
Introduction
205(1)
Comparisons of Paired Means
206(16)
Least Significant Difference Test
206(12)
Duncan's Multiple-Range Test (DMRT)
218(4)
Comparisons of Grouped Means
222(17)
Orthogonal Class Comparisons
223(6)
Trend Comparisons
229(10)
Sample Designs Over Time
239(26)
Terminology and Concepts
239(2)
Representing Time Spans
240(1)
Analysis of Experiments over Years
241(8)
Analysis of Experiments over Seasons
249(16)
Regression and Correlation Analysis
265(52)
Bivariate Relationships
265(1)
Regression Analysis
266(12)
Correlational Analysis
278(9)
Curvilinear Regression Analysis
287(12)
Multiple Regression and Correlation
299(18)
Covariance Analysis
317(34)
Introduction
317(4)
Covariance Analysis Procedures
321(19)
Completely Randomized Design (CRD)
321(5)
Randomized Complete Block (RCB) Design
326(5)
Split-Plot Design
331(9)
Estimating Missing Data
340(11)
Appendix A Chi-Square Distribution 351(2)
Appendix B The Arc SineTransformation 353(4)
Appendix C Selected Latin Squares 357(4)
Appendix D Random Digits 361(2)
Appendix E Points for the Distribution of F 363(8)
Appendix F Basic Plans for Balanced and Partially Balanced Lattice Designs 371(12)
Appendix G Fractional Factorial Design Plans 383(24)
Appendix H Significant Studentized Ranges for 5% and 1% Level New Multiple Range Test 407(4)
Appendix I Student t Distribution 411(2)
Appendix J Coefficients and the Sum of Squares of Sets of Orthogonal Polynomials When There Are Equal Interval Treatments 413(2)
Appendix K Minitab 415(12)
Index 427


Reza Hoshmand (Author)
Biežāk uzdotie jautājumi par e-grāmatām Biežāk uzdotie jautājumi par e-grāmatām
Permanent link: https://www.kriso.lv/db/97814200106402e.html
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