Good Statistical Practice for Natural Resources Research,9780851997223

Good Statistical Practice for Natural Resources Research

by ; ; ;
ISBN13: 9780851997223
ISBN10: 0851997228
Format: Paperback
Pub. Date: 2004-09-02
Publisher(s): Cab Intl
List Price: $98.39

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Summary

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.

Table of Contents

Preface xi
Acknowledgements xiii
Contributors xv
Abbreviations xvii
Part 1: Introduction
1(30)
What is Natural Resources Research?
3(10)
Key Features
3(2)
Examples
5(1)
Where Does Statistics Fit In?
6(2)
Types of Study
8(1)
Is It Research?
9(1)
Who Is This Book For?
10(3)
At Least Read This. . .
13(8)
Statistical Considerations
13(1)
The Planning Phase
14(2)
The Data
16(1)
The Analysis
17(2)
The Presentation of Results
19(1)
Is This Enough?
19(2)
Sidetracks
21(10)
Introduction
21(1)
The Research Team
22(2)
Project Management
24(1)
Statistical and Research Approaches
24(4)
Research and Professional Ethics
28(3)
Part 2: Planning
31(100)
Introduction to Research Planning
33(8)
Introduction
33(1)
Linking Activities and Picturing Strategies
33(2)
Priorities
35(2)
Problem Domains and Research Locations
37(1)
Iterative Planning and the Activity Protocol
38(3)
Concepts Underlying Experiments
41(24)
Introduction
41(1)
Specifying the Objectives
42(2)
Selection of Treatments
44(8)
Choosing the Units
52(2)
Replication -- What, Why and How Much?
54(3)
Choice of Sites
57(1)
Choosing the Blocks
58(1)
Allocating Treatment to Units
59(1)
Taking Measurements
60(2)
Analysis and Data Management Issues that Affect Design
62(1)
Taking Design Seriously
63(2)
Sampling Concepts
65(22)
Introduction
65(1)
Concepts of Good Sampling Practice
65(3)
Study Objectives
68(3)
Units
71(3)
Comparative Sampling
74(2)
Sample Size
76(1)
Stratification -- Getting It Right
77(2)
Doing One's Best with Small Samples
79(1)
Impact Assessment
80(2)
Common (and Not So Common!) Sampling Methods
82(4)
Putting Sampling in Context
86(1)
Surveys and Studies of Human Subjects
87(20)
Introduction
87(1)
Surveys
88(2)
Good Survey Practice
90(4)
Study Management
94(1)
Participatory Research
95(1)
Doing One's Best with Small Samples
96(2)
Site Selection in Participatory Research
98(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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