This module consists of three units viz., Research Methods, Scientific Writing and Communication Skills and Statistics and Biometry. This module presents an in depth knowledge of statistics, biometry and research methodology The module is designed to introduce learners to the fields of statistical research in Agricultural Sciences. Concepts on ethics and philosophy of science, and scientific writing skills will be introduced. Advanced statistical methods, experimental design, data collection, data exploration and analyses will form part of the modules.
Indicative Content includes
· Ethics in research · Philosophy of science · Research methods
· The scientific writing process · Preparation of scientific presentations
· Presentation and communication of scientific research results
· Principles of experimental design and census techniques
· Design of field experiments – characteristics, merits and limitations
· Statistical tools – tests and report of results · Data exploration
· Distributions - (Normal vs. other and data transformation)
· Regression analysis and analysis of variance · Analysis of categorical data
· Missing data · Principles of experimentation · Generalized Linear Models
· Mixed Linear Models · Restricted Maximum Livelihood (REML)
· Multivariate analysis - Principal Components Analysis (PCA)
- Discriminant analysis - Cluster analysis ; Genotype × environment Interaction Analysis
Indicative Resources
· Statistical computer package program:
· SAS
· Genstat
· Minitab
14. Indicative Resources
Core text:
1. Creswell J. W., 1994. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. 2nd Edition, 272 pages
2. Bryman, A. 2001. Social Research Methods. Second Edition. 748 pages
3. Creswell, J.W. 2006. Designing and Conducting Mixed Methods Research.275 pages
4.Grbich, C. 2007. Qualitative Data Analysis: An Introduction
5. Blaxter, L., Hughes, C. and Tight, M. (2006, 3rd ed) How to research, Buckingham: Open University.
6. Bell, J. (2005, 4th ed) Doing your research project: A guide for first-time researchers in education and social sciences, Buckingham: Open University Press.
7. Booth, W.C., Colomb, G.G., & Williams, J.M. (2003) The craft of research, Chicago: University of Chicago Press (Chicago Guides to Writing, Publishing and Editing).
8. Bryman, A. & Bell, E. (2003) Business research methods, Oxford: Oxford University Press. Also see companion website below.
9. Denscombe, M. (2003, 2nd ed) The good research guide: For small-scale social research projects, Buckingham: Open University.
10. Field, A. & Hole, G.J. (2002) How to design and report experiments, London: Sage.
11. Hart, (1998) Doing the literature review: releasing the social science research imagination, Sage: London.
12. Murray, R. (2006, 2nd ed) How to write a thesis, Buckingham: Open University Press.
13. Rudestam, K. & Newton, R. (2000, 2nd ed) Surviving your dissertation: A comprehensive guide to content and process, London: Sage.
14. Swetnam, D. (2000, 3rd ed) Writing your dissertation.
15. White, B. (2003) Dissertation skills for business and management students, Thompson Learning.
16. Fan J., and R. Li. 2000. Advanced Applied Statistics
17. Seltman, H. J. 2014. Experimental Design andAnalysis
18. Kang, M. S. (Ed). 2002. Quantitative Genetics, Genomics and Plant Breeding. CABI Publishing. New York, NY.
19. Shalabh, H. T. 2009. Statistical Analysis of Designed Experiments. 3rd Edition. Springer, New York
20. Robert, O. K. 2000. Design of Experiments: Statistical Principles of Research and Analysis. 2nd Edition. Thomson Learning. USA
21. Fan J., and R. Li. 2000. Advanced Applied Statistics
22. Seltman, H. J. 2014. Experimental Design andAnalysis
23. Kang, M. S. (Ed). 2002. Quantitative Genetics, Genomics and Plant Breeding. CABI Publishing. New York, NY.
24. Shalabh, H. T. 2009. Statistical Analysis of Designed Experiments. 3rd Edition. Springer, New York
25. Robert, O. K. 2000. Design of Experiments: Statistical Principles of Research and Analysis. 2nd Edition. Thomson Learning. USA
15. Background Texts
Journal articles:
· Biometrika
· Journal of Statistical Education
· Statistics in practice
· International Journal of Experimental Design and Process Optimization
· American Journal of Theoretical and Applied Statistics
Key websites and on-line resources:
http://www.esrc.ac.uk/funding-and-guidance/tools-and-resources/research-resources/index.aspx
http://www.lrs.org/resources.php
http://www.methodspace.com/page/about-this-space
http://www.socialresearchmethods.net/
http://www.experiment-resources.com/
http://www.amstat.org/education/usefulsitesforteachers.cfm
http://statistics-help-for-students.com/
https://www.khanacademy.org/math/probability
https://learnandteachstatistics.wordpress.com/
http://www.amstat.org/publications/jse/v6n3/smith.html
https://www.udacity.com/course/intro-to-statistics--st101
Learning Outcomes
1. Having successfully completed the module, learners should be able to demonstrate a thorough understanding of:
· Ethical considerations in research
· Philosophy of science
· How to choose and develop proper research projects
2. Learners should demonstrate a comprehensive understanding of relevant techniques and approaches applicable to the research
3. Learners should demonstrate a clear understanding of how established techniques of research and enquiry are used in the discipline
4. How to formulate hypotheses and to design tests of hypotheses
5. Experimental design
6. Data collection
7. Data exploration and handling of data
8. Interpretation and reporting of results
· Apply a range of standard and specialised research techniques of enquiry
· Plan and carry out a research or development project.
· Communicate their research to wide range of audience with some levels of expertise
· Communicate with peers, more senior colleagues and specialists
· Use a wide range of appropriate software for presentation/communication to the audience
· Evaluate a wide range of numerical and graphical information
· Synthesise and critically analysing the content of a scientific paper
· Use an appropriate experimental design and sampling schedule.
· Use an appropriate statistical method to analyse data, evaluate and report the results.
Research Methodology and Biometry