Data analysis manual for coconut researchers

This publication on ”Data Analysis Manual for Coconut Researchers” provides basic statistical concepts and includes: sampling methods, frequency distribution of observations, estimation and tests of significance, analysis and relationships between variables, basic principles for planning and conducting coconut field trials, basic experimental designs for coconut trials, experimental designs for coconut trials with modified blocking, experimental designs for multiple factors, analysis of multilocation trials, and multivariate analysis and determination of genetic distance. The manual provide details of experimental designs to use in agronomic, breeding trails and germplasm characterization and evaluation. The data used for most of the examples in this manual are actual research data on coconut generated at the Central Plantation Crops Research Institute (CPCRI), Kasaragod, India. Almost all the analyses described in this manual have been described with some suitable examples and step-by-step procedures. Using this tutorial-type manual, coconut researchers as well as other researchers can practice computation by themselves using the examples provided in this manual and then use the same procedure to analyze their own data.The manual also include introduction to 'R' and its use to perform statistical analysis for data presentation in this manual and are presented as Appendices. The objective of the appendices is to explain how the 'R' statistical software can be used to perform the analyses presented in the manual. Data in the Tables of this manual have been copied into text files readable by 'R'. The contents of these text files are printed at the end of respective appendices. A gray background is sued for 'R' commands and a frame with white background for the results returned by 'R'. It is easy to test the 'R' commands by copying the text of the gray areas into the 'R' console. It is therefore expected that this publication will help the scientific community to better plan and manage their experiments and, analyze and interpret their experimental data.