Good Statistical Practice for Natural Resources Research

, by Roger D. Stern; Richard Coe; Eleanor F. Allan; Ian C. Dale

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ISBN: 9780851997223 | 0851997228
Cover: Paperback
Copyright: 9/2/2004

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This book provides a practical approach to applying statistics to a wide variety of studies or projects. It will help bring together the biophysical and socioeconomic aspects, that are increasingly seen as integral to successful natural resources management. The topics covered include types of study in NRM, planning, data management and analysis. The book has been written for advanced students and professionals in all disciplines in agriculture, forestry, rural development, environmental and related sciences.

Preface

Acknowledgements

xiii

Contributors

Abbreviations

xvii

Part 1: Introduction

(30)

What is Natural Resources Research?

(10)

Key Features

(2)

Examples

(1)

Where Does Statistics Fit In?

(2)

Types of Study

(1)

Is It Research?

(1)

Who Is This Book For?

(3)

At Least Read This. . .

(8)

Statistical Considerations

(1)

The Planning Phase

(2)

The Data

(1)

The Analysis

(2)

The Presentation of Results

(1)

Is This Enough?

(2)

Sidetracks

(10)

Introduction

(1)

The Research Team

(2)

Project Management

(1)

Statistical and Research Approaches

(4)

Research and Professional Ethics

(3)

Part 2: Planning

(100)

Introduction to Research Planning

(8)

Introduction

(1)

Linking Activities and Picturing Strategies

(2)

Priorities

(2)

Problem Domains and Research Locations

(1)

Iterative Planning and the Activity Protocol

(3)

Concepts Underlying Experiments

(24)

Introduction

(1)

Specifying the Objectives

(2)

Selection of Treatments

(8)

Choosing the Units

(2)

Replication -- What, Why and How Much?

(3)

Choice of Sites

(1)

Choosing the Blocks

(1)

Allocating Treatment to Units

(1)

Taking Measurements

(2)

Analysis and Data Management Issues that Affect Design

(1)

Taking Design Seriously

(2)

Sampling Concepts

(22)

Introduction

(1)

Concepts of Good Sampling Practice

(3)

Study Objectives

(3)

Units

(3)

Comparative Sampling

(2)

Sample Size

(1)

Stratification -- Getting It Right

(2)

Doing One's Best with Small Samples

(1)

Impact Assessment

(2)

Common (and Not So Common!) Sampling Methods

(4)

Putting Sampling in Context

(1)

Surveys and Studies of Human Subjects

(20)

Introduction

(1)

Surveys

(2)

Good Survey Practice

(4)

Study Management

(1)

Participatory Research

(1)

Doing One's Best with Small Samples

(2)

Site Selection in Participatory Research

(2)

Data Collection in Participatory Research

100

(2)

Combination of Studies

102

(3)

Targeted Sampling

105

(2)

Surveying Land and Natural Populations

107

(10)

Introduction

107

(2)

Sampling in Space

109

(1)

Multiscale Measurement

110

(1)

Replication May Be Difficult

111

(1)

Time and Repeated Sampling

112

(3)

Special Methods

115

(2)

Planning Effective Experiments

117

(14)

Introduction

117

(1)

Types of On-farm Experiments

118

(1)

Specifying Objectives

118

(2)

Choice of Farms and Villages

120

(1)

Choice of Treatments and Units

121

(8)

Measurements

129

(1)

Other Considerations

130

(1)

Part 3: Data Management

131

(72)

Data Management Issues and Problems

133

(18)

Introduction

133

(1)

What We Mean by `Data'

134

(2)

Software for Handling Data

136

(1)

Database Structure

137

(1)

Qualitative Data

138

(2)

Designing a Data Entry System

140

(1)

Data Entry and Checking

141

(3)

Organizing the Data for Analysis

144

(1)

Analysis

145

(1)

Audit Trail

146

(1)

Backing Up

147

(1)

Archiving

148

(1)

In Conclusion

149

(2)

Use of Spreadsheet Packages

151

(16)

Introduction

151

(1)

Common Problems with Data Entry

152

(2)

Facilitating the Data Entry Process

154

(6)

The Metadata

160

(3)

Checking the Data After Entry

163

(2)

Conclusions

165

(2)

The Role of a Database Package

167

(20)

Introduction

167

(1)

Data Management in Excel

167

(6)

Components of a Database Package

173

(11)

The Data Flow

184

(1)

Adopting a Database Approach

185

(2)

Developing a Data Management Strategy

187

(10)

Introduction

187

(1)

Requirements for Building a Data Management Strategy

187

(5)

Data Policy

192

(3)

Data Management Plan

195

(1)

Further Points

195

(2)

Use of Statistical Software

197

(6)

Introduction

197

(1)

A Strategy

198

(2)

Which Statistics Packages Could Be Used?

200

(3)

Part 4: Analysis

203

(150)

Analysis -- Aims and Approaches

205

(14)

Taking Control

205

(1)

Qualitative or Quantitative Analysis

206

(2)

Steps

208

(1)

Resources for Analysis

209

(1)

What Do You Need to Know?

210

(1)

Getting Started

211

(8)

The DIY Toolbox -- General Ideas

219

(28)

Opening the Toolbox

219

(1)

Summaries to Meet Objectives

219

(4)

Response Variables and Appropriate Scales

223

(1)

Doing the Exploratory Analysis

224

(4)

Understanding Uncertainty

228

(6)

Hypothesis Testing and Significance

234

(4)

Analysis of Variance

238

(3)

A General Framework

241

(1)

Consequences for Analysis

242

(5)

Analysis of Survey Data

247

(18)

Preparing for the Analysis

247

(1)

Data Structure

248

(7)

Doing the Analysis

255

(10)

Analysis of Experimental Data

265

(18)

Strategy for Data Analysis

265

(1)

The Essentials of Data Analysis

265

(9)

Complications in Experiments

274

(1)

Multiple Levels

275

(2)

Repeated Measures Made Easy

277

(2)

Surprise Complications

279

(2)

What Next?

281

(2)

General Linear Models

283

(16)

Introduction

283

(1)

A Simple Model

283

(3)

Further Information about the Model

286

(2)

Steps in Statistical Modelling

288

(1)

A Model with Factors

289

(4)

Analysing Other Designs

293

(1)

One Further Model

293

(4)

Assumptions Underlying the Model

297

(1)

The Linear Model Language

298

(1)

The Craftsman's Toolbox

299

(38)

Introduction

299

(1)

Visualization

299

(7)

Multivariate Methods

306

(10)

General Ideas on Modelling

316

(6)

Broadening the Class of Models

322

(5)

Mixed Models and More

327

(5)

Back to Reality

332

(5)

Informative Presentation of Tables, Graphs and Statistics

337

(16)

Introduction

337

(1)

Nine Basic Points

337

(1)

Graphs and Charts

338

(3)

Tables

341

(4)

Results of Statistical Analysis

345

(6)

Data Quality Reporting

351

(1)

In Conclusion

352

(1)

Part 5: Where Next?

353

(26)

Current Trends and their Implications for Good Practice

355

(10)

Introduction

355

(1)

Trends in Planning

355

(1)

Trends in Data Management

356

(2)

Developments in Methods of Analysis

358

(1)

Communicating the Results

359

(1)

Progress in Training Methods

360

(5)

Resources and Further Reading

365

(14)

Introduction

365

(1)

Adding to this Book

365

(1)

The Bookshelf

366

(7)

SSC Web-based Resources

373

(2)

ICRAF Web-based Resources

375

(2)

Statistical, Graphical and Data Management Software

377

(2)

Appendix: Preparing a Protocol

379

(6)

Index

385

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Good Statistical Practice for Natural Resources Research

Summary

Table of Contents

Supplemental Materials