These guides are now quite old, i.e. produced between 1998 and 2006. They are short guides on the topics given below: We then produced a book in 2004 - which we now have permission also to include if we wish.
Given our aims in ADI I suggest some of these guides still have value. They would be more useful if we now added an update on some of the topics that have moved on since they were written. This includes on-farm advances through O by C, data collection through ODK, and also aspects of analysis (with R?) which was only just starting as these guides were written.
However, what do you think? I have the pdf files and also a help version that could also be edited easily. Here is the list:
Guides to Statistical Good Practice
This series of biometric guidelines was written for people working on projects dealing with renewable natural resources, but have been useful more widely. The guidelines were produced by the Statistical Services Centre at The University of Reading, UK, with support from DFID.
The guides are the product of a team effort involving Roger Stern, Savitri Abeyasekera, Ian Wilson, Eleanor Allan, Cathy Garlick, Sandro Leidi, Carlos Barahona and Ian Dale, with contributions from Bob Burn, Ric Coe, Sian Floyd, James Gallagher, Joan Knock, Roger Mead, Clifford Pearce, John Rowlands, John Sherington and others. We welcome your comments on any aspect of the guides.
Overview Guide:
Statistical Guidelines for Natural Resources Projects
Guides concerned with Planning:
The Design of Experiments
Some Basic Ideas of Sampling
Guidelines for Planning Effective Surveys
On-Farm Trials - Some Biometric Guidelines
One Animal per Farm
Guides on Data Handling and Management:
Data Management Guidelines for Experimental Projects
Excel for Statistics: Tips and Warnings (probably omit)
Disciplined Use of Spreadsheets for Data Entry
The Role of a Database Package in Managing Research Data
Project Data Archiving - Lessons from a Case Study (omit)
Moving on from MSTAT (omit)
Guides on Analysis:
Confidence & Significance: Key Concepts of Inferential Statistics
The Statistical Background to ANOVA (omit)
Modern Approaches to the Analysis of Experimental Data
Approaches to the Analysis of Survey Data
Modern Methods of Analysis
Mixed Models and Multilevel Data Structures in Agriculture
Guides on Presentation:
Informative Presentation of Tables, Graphs and Statistics
Good Tables for Excel Users
Good Statistical Graphics in Excel
These guides are now quite old, i.e. produced between 1998 and 2006. They are short guides on the topics given below: We then produced a book in 2004 - which we now have permission also to include if we wish.
Given our aims in ADI I suggest some of these guides still have value. They would be more useful if we now added an update on some of the topics that have moved on since they were written. This includes on-farm advances through O by C, data collection through ODK, and also aspects of analysis (with R?) which was only just starting as these guides were written.
However, what do you think? I have the pdf files and also a help version that could also be edited easily. Here is the list:
Guides to Statistical Good Practice
This series of biometric guidelines was written for people working on projects dealing with renewable natural resources, but have been useful more widely. The guidelines were produced by the Statistical Services Centre at The University of Reading, UK, with support from DFID.
The guides are the product of a team effort involving Roger Stern, Savitri Abeyasekera, Ian Wilson, Eleanor Allan, Cathy Garlick, Sandro Leidi, Carlos Barahona and Ian Dale, with contributions from Bob Burn, Ric Coe, Sian Floyd, James Gallagher, Joan Knock, Roger Mead, Clifford Pearce, John Rowlands, John Sherington and others. We welcome your comments on any aspect of the guides.
Overview Guide: Statistical Guidelines for Natural Resources Projects
Guides concerned with Planning: The Design of Experiments Some Basic Ideas of Sampling Guidelines for Planning Effective Surveys On-Farm Trials - Some Biometric Guidelines One Animal per Farm
Guides on Data Handling and Management: Data Management Guidelines for Experimental Projects Excel for Statistics: Tips and Warnings (probably omit) Disciplined Use of Spreadsheets for Data Entry The Role of a Database Package in Managing Research Data Project Data Archiving - Lessons from a Case Study (omit) Moving on from MSTAT (omit)
Guides on Analysis: Confidence & Significance: Key Concepts of Inferential Statistics The Statistical Background to ANOVA (omit) Modern Approaches to the Analysis of Experimental Data Approaches to the Analysis of Survey Data Modern Methods of Analysis Mixed Models and Multilevel Data Structures in Agriculture
Guides on Presentation: Informative Presentation of Tables, Graphs and Statistics Good Tables for Excel Users Good Statistical Graphics in Excel