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Practical Statistics and Experimental Design for Plant and Crop Science

by: Clewer, Alan G.; Scarisbrick, David H.

Practical Statistics and Experimental Design for Plant and Crop Science

by: Clewer, Alan G.; Scarisbrick, David H.

ISBN 13:
9780471899099
ISBN 10:
0471899097
Edition: 1st
Format: Paperback
Copyright: 02/08/2001
Publisher: WILEY

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Summary

Presents readers with a user-friendly, non-technical introduction to statistics and the principles of plant and crop experimentation. Avoiding mathematical jargon, it explains how to plan and design an experiment, analyse results, interpret computer output and present findings. Using specific crop and plant case studies, this guide presents: * The reasoning behind each statistical method is explained before giving relevant, practical examples * Step-by-step calculations with examples linked to three computer packages (MINITAB, GENSTAT and SAS) * Exercises at the end of many chapters * Advice on presenting results and report writing Written by experienced lecturers, this text will be invaluable to undergraduate and postgraduate students studying plant sciences, including plant and crop physiology, biotechnology, plant pathology and agronomy, plus ecology and environmental science students and those wanting a refresher or reference book in statistics.

Preface

Basic Principles of Experimentation

(8)

Introduction

(1)

Field and glasshouse experiments

(2)

Choice of site

(1)

Soil testing

(1)

Satellite mapping

(1)

Sampling

(3)

Basic Statistical Calculations

(7)

Introduction

(1)

Measurements and type of variable

(1)

Samples and populations

(6)

Basic Data Summary

(8)

Introduction

(1)

Frequency distributions (discrete data)

(2)

Frequency distributions (continuous data)

(4)

Descriptive statistics

(2)

The Normal Distribution, the t-Distribution and Confidence Intervals

(14)

Introduction to the normal distribution

(1)

The standard normal distribution

(2)

Further use of the normal tables

(2)

Use of the percentage points table (Appendix 2)

(1)

The normal distribution in practice

(2)

Introduction to confidence intervals

(1)

Estimation of the population mean

(1)

The sampling distribution of the mean, μ

(1)

Confidence limits for μ when σ is known

(2)

Confidence limits for μ when σ is unknown---use of the t-distribution

(2)

Determination of sample size

(1)

Estimation of total crop yield

(2)

Introduction to Hypothesis Testing

(11)

The standard normal distribution and the t-distribution

(1)

The single sample t-test

(3)

The P-value

(1)

Type I and Type II errors

(1)

Choice of level of significance

(1)

The usefulness of a test

(1)

Estimation versus hypothesis testing

(1)

The paired samples t-test

(3)

Comparison of Two Independent Sample Means

(14)

Introduction

(2)

The Independent Samples t-test

(4)

Confidence intervals

(1)

The theory behind the t-test

(3)

The F-test

(1)

Unequal sample variances

(1)

Determination of sample size for a given precision

(3)

Linear Regression and Correlation

(24)

Basic principles of Simple Linear Regression (SLR)

(3)

Experimental versus observational studies

(1)

The correlation coefficient

(1)

The least squares regression line and its estimation

(4)

Calculation of residuals

(1)

The goodness of fit

(2)

Calculation of the correlation coefficient

(1)

Assumptions, hypothesis tests and confidence intervals for simple linear regression

(8)

Testing the significance of a correlation coefficient

(4)

Curve Fitting

(15)

Introduction

(1)

Polynomial fitting

(2)

Quadratic regression

(4)

Other types of curve

(7)

Multiple linear regression

100

(2)

The Completely Randomised Design

102

(30)

Introduction

102

(1)

Design construction

103

(2)

Preliminary analysis

105

(3)

The one-way analysis of variance model

108

(2)

Analysis of variance

110

(8)

After Anova

118

(5)

Reporting results

123

(1)

The completely randomised design---unequal replication

124

(4)

Determination of number of replicates per treatment

128

(4)

The Randomised Block Design

132

(17)

Introduction

132

(3)

The analysis ignoring blocks

135

(1)

The analysis including blocks

136

(1)

Using the computer

136

(1)

The effect of blocking

137

(1)

The randomised blocks model

138

(3)

Using a hand calculator to find the sums of squares

141

(1)

Comparison of treatment means

142

(2)

Reporting the results

144

(1)

Deciding how many blocks to use

144

(2)

Plot sampling

146

(3)

The Latin Square Design

149

(10)

Introduction

149

(2)

Randomisation

151

(2)

Interpretation of computer output

153

(2)

The Latin square model

155

(1)

Using your calculator

156

(3)

Factorial Experiments

159

(23)

Introduction

159

(1)

Advantages of factorial experiments

160

(3)

Main effects and interactions

163

(2)

Varieties as factors

165

(1)

Analysis of a randomised blocks factorial experiment with two factors

166

(10)

General advice on presentation

176

(1)

Experiments with more than two factors

177

(2)

Confounding

179

(1)

Fractional replication

180

(2)

Comparison of Treatment Means

182

(31)

Introduction

182

(1)

Treatments with no structure

182

(9)

Treatments with structure (factorial structure)

191

(4)

Treatments with structure (levels of a quantitative factor)

195

(7)

Treatments with structure (contrasts)

202

(11)

Checking the Assumptions and Transformation of Data

213

(13)

The assumptions

213

(6)

Transformations

219

(7)

Missing Values and Incomplete Blocks

226

(12)

Introduction

226

(1)

Missing values in a completely randomised design

226

(3)

Missing values in a randomised block design

229

(5)

Other types of experiment

234

(1)

Incomplete block designs

234

(4)

Split Plot Designs

238

(18)

Introduction

238

(1)

Uses of this design

238

(2)

The skeleton analysis of variance tables

240

(2)

An example with interpretation of computer output

242

(8)

The growth cabinet problem

250

(2)

Other types of split plot experiment

252

(1)

Repeated measures

252

(4)

Comparison of Regression Lines and Analysis of Covariance

256

(16)

Introduction

256

(1)

Comparison of two regression lines

256

(4)

Analysis of covariance

260

(1)

Analysis of covariance applied to a completely randomised design

260

(5)

Comparing several regression lines

265

(5)

Conclusion

270

(2)

Analysis of Counts

272

(21)

Introduction

272

(1)

The binomial distribution

272

(3)

Confidence intervals for a proportion

275

(2)

Hypothesis test of a proportion

277

(2)

Comparing two proportions

279

(1)

The chi-square goodness of fit test

280

(4)

r x c contingency tables

284

(2)

2 x c contingency tables: comparison of several proportions

286

(1)

2 x 2 contingency tables: comparison of two proportions

287

(2)

Association of plant species

289

(1)

Heterogeneity chi-square

290

(3)

Some Non-parametric Methods

293

(14)

Introduction

293

(1)

The Sign test

294

(2)

The Wilcoxon single-sample test

296

(1)

The Wilcoxon matched pairs test

297

(2)

The Mann-Whitney U test

299

(3)

The Kruskal-Wallis test

302

(2)

Friedman's test

304

(3)

Appendix 1: The normal distribution function

307

(1)

Appendix 2: Percentage points of the normal distribution

308

(1)

Appendix 3: Percentage points of the t-distribution

309

(1)

Appendix 4a: 5 per cent points of the F-distribution

310

(2)

Appendix 4b: 2.5 per cent points of the F-distribution

312

(2)

Appendix 4c: 1 per cent points of the F-distribution

314

(2)

Appendix 4d: 0.1 per cent points of the F-distribution

316

(2)

Appendix 5: Percentage points of the sample correlation coefficient (r) when the population correlation coefficient is 0 and n is the number of X, Y pairs

318

(1)

Appendix 6: 5 per cent points of the Studentised range, for use in Tukey and SNK tests

319

(2)

Appendix 7: Percentage points of the chi-square distribution

321

(1)

Appendix 8: Probabilities of S or fewer successes in the binomial distribution with n `trials' and p=0.5

322

(1)

Appendix 9: Critical values of T in the Wilcoxon signed rank or matched pairs test

323

(1)

Appendix 10: Critical values of U in the Mann-Whitney test

324

(3)

References

327

(1)

Amazon no longer offers textbook rentals. We do!

Practical Statistics and Experimental Design for Plant and Crop Science

Practical Statistics and Experimental Design for Plant and Crop Science

9780471899099

0471899097

Summary

Author Biography

Table of Contents

Supplemental Materials

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