AGRI3121: Research Methods and Data Management

Welcome to the module "Research Methods and Data Management". This is a module to be taught to Year III Agribusiness students. It is made up of two components such as "Research Methods, Data Management and Data Analysis and Software Application". 

Aim:

(i) The main objective of this course is to make the student able to design, to implement  & organize, to carry out and to write various research tasks.

(ii) To make student familiar with basic knowledge of Data Management; Data collection and Analysis and application of software in problems solving

Learning Outcomes 

Knowledge and Understanding

          Having successfully completed the module, students should be able to:

understand mathematical and statistical models explaining social behavior

Improved critical thinking capacity

Improving the mathematical tools in economics and more particularly in development economics

Manipulate Data using various software

Cognitive/Intellectual skills/Application of Knowledge

Having successfully completed the module, students should be able to:

Analyze problems with help of appropriate tools and define and evaluate relations between all aspects

Economic  Analysis  of data using some mathematical  models

Communication/ICT/Numeracy/Analytic Techniques/Practical Skills

          Having successfully completed the module, students should be able to:

Write a report

Present the results

Have practice in discussion and reasoning

Compile a literature review and make an appropriate use of references

General transferable skills

          Having successfully completed the module, students should be able to:

Independently carry out a field survey

Apply basic tools of Data Management and Research Methods

 Learning and Teaching Strategies

The learning and teaching strategy will comprise: lectures, field visits, self-studies, seminars and presentations. The total student hours for the module are 200 hours. The contact hours where students and teacher meet face to face (lectures seminars/workshops, practical classes/stock laboratory) have been allocated 48 hours each which is less than a half of the total hours budgeted for the module.

Practical assignments will be given to students to test for their understanding of the major concepts developed in class. ICT labo practices will be organised to introduce students to manipulate and analyse data. Tutorial problems are solved in-group work (each group consists of not more than 10 students), presented and discussed in class aiming at encouraging student to participate in the teaching and learning process. The e-learning methodology will be encouraged.

Assessment Strategy

Examination: Continuous Assessment Tests (CAT) and final examination. Examinations will cover lectures, assigned reading materials, and discussions;

The assignments will be graded on individual basis and on each component of the module;

ICT labo work will be evaluated.

 Assessment Pattern:

Two assessments for the module:- The course work assessment, test, quiz will carry 50% and the course final examination will carry 50%.

Strategy for feedback and student support during module:

After the first few weeks in course assessment the module teaching team should meet with the students and exchange with them concerning their performance in the already evaluated courses in order to improve the future performance. During the meeting, the module team should encourage students to give their opinions on how to improve their performance

Indicative Resources:

The following textbooks are recommended for reading:

Eric L. Einspruch (2005). An introductory guide to SPSS for Windows, 2^nd ed. Sage Publications, Inc. ISBN 1-4129-0415-3

Gilat A. MATLAB. An Introduction with Applications. Fourth edition. Ohio.USA

 Joaquim P. Marques de Sá (2007). Applied Statistics Using SPSS, STATISTICA,MATLAB and R. Springer Berlin Heidelberg New York. ISBN 978-3-540-71971-7

Peter Dalgaard (2008). Introductory Statistics with R, 2^nd ed. Springer Science+Business Media, LLC. e-ISBN: 978-0-387-79054-1

Prabhanjan Narayanachar Tattar, Suresh Ramaiah & B.G. Manjunath (2016). A course in statistics with R. John Wiley & Sons, Ltd. ISBN: 9781119152729

Sabine Landau and Brian S. Everitt (2004). A handbook of statistical analyses using SPSS. Chapman & Hall/CRC Press LLC. ISBN 1-58488-369-3

Sally A. Lesik (2010). Applied Statistical Inference with MINITAB. CRC Press, Taylor & Francis Group. ISBN-13: 978-1-4200-6584-8 (eBook - PDF)

Trevor Wegner (2013). Applied Business Statistics Methods and Excel-based Applications, 3^rd Ed. Juta and Company Ltd.  ISBN: 978 0 7021 9709 3 (Web PDF).

Wim Buysse, Roger Stern and Ric Coe (2004). GenStat Discovery Edition for everyday use. World Agroforestry Centre. ISBN 92 9059 158 7