Internship Report

HIGHER INSTITUTE OF AGRICULTURE & ANIMAL PRODUCTION (ISAE) DEPARTMENT OF RURAL DEVELOPMENT & AGRIBUSINESS (RDA) COURSE:RESEARCH METHODOLOGY (RM) CREDITS:3 = 45 hrs (30 Theory + 15 TP) CLASS:RDA 4th Yr, Aug 2012 VENUE:Rubilizi Campus, CONVENOR:Dr. J. Richard N. KANYARUKIGA PhD (IWRM), UDSM, Tanzania; MSc TAD (AE&P), Reading, UK; BSc Agric (AS&P), SUA, Morogoro, Tanzania Contact:Tel: +250 785 437 335; E-mail:[email protected] ac. rw [email protected] com kf. [email protected] com ————————————————- Course objectives: Main Objective: To provide conceptual and practical guidelines on how to conduct research, in a manner consistent with scientific research methodology. Specific objectives: 1. To equip students with the understanding of the concepts of RESEARCH from perspectives of: i. Research community itself (students, lecturers/researchers, reviewers, etc. ) ii. Research users/clients: especially: ) Policy-makers who commission research or manage calls for tender b) Evaluators and reviewers who are involved in awarding research contracts and c) Other research funders, including public and private agencies, charitable foundations, companies and NGOs. * To equip students with skills & capabilities to conduct research relevant to for Rural Development & Agribusiness in our country; and in a manner compliant professional standards. Course structure & organization a) 3 Units @ 10 hrs of theory lecture ) 2 Units @ 5 hrs of 1 INDIVIDUAL & 1 GROUP essay write up c) 1 Unit of 5 hrs Class presentations d) GRADING: e) 40%: 2 Essays & Class presence/presentations f) 60%: Terminal exam COURSE I:INTRODUCTION: The Basics of Research Methodology ————————————————- Refer Lecture Notes: Evison Bhebhe (2009). Socio-Economic Research Methods 1. Meaning of research 2. Mission of research 3. Reasons/ Importance of research 4. General steps of research process 5. Research philosophy 1) Positivism 2) Interpretivism . Classification/Taxonomy of research methodologies 3) Laboratory experimentation 4) Field experimentation – subjective/argumentative 5) Surveys – Action research 6) Case studies – case studies 7) Theorem proof – descriptive/interpretive 8) Forecasting – future research 9) Simulation – role/game playing 10) Action research 7. Research problems, hypotheses & research objectives II:RESEARCH STATISTICSS: The Basics of Research Statistics ————————————————- Refer Text Book: Kothari, CK (…. ). Research Methodology ———————————————— Also: Msambichaka, LA (1992). Methods & techniques for agriculture & RD analysis – a handbook for functional managers 1. Introduction * There are many problems in rural areas which need systematic investigation * Thus, data collection, processing & analysis becomes essential * This section attempts to discuss: * Data collection; and * Most basic statistical tools to use 2. Data collection: 3. 1. Questionnaire (schedule) design (Dos & Don’ts) When preparing a questionnaire consider the following: i.

Questions to be simple & clear ii. Design questions to obtain objective answers that may be tabulated iii. Make instructions & definitions precise so that enumerator doesn’t doubt info required; or statistical tool to use iv. Arrange questions in logical sequence; each question facilitating answer to subsequent question. Do not allow questions to skip back and forth. Frame one topic after another v. Avoid leading questions vi. Do not lose your head if you get unsatisfactory answers resulting from your questions 3. 2. Sampling method

When selecting a sampling method, choose data which will provide a sample as representative as possible to get realistic conclusions: i. (Simple) Random sampling: * assumes that each time an item (sample size n from N population) is selected, each of those items has an equal chance or the same probability of being selected. * Selection of random numbers is facilitated by the use of a table of random numbers (Appendix I) – whereby picking 2 digits is recommended. ii. Systematic sampling: * Sample size determined in advance * Basic list (not necessarily numbered) is prepared; Next, sampling ratio or sampling fraction is computed – expressed as 1 in n (round numbers) * Figure k used as sampling interval; i. e. every k-th item in the list, starting from any random begun with iii. Cluster sampling: * Sub-divides population into grps or clusters of individuals * Then gets sample by using simple random sampling * Sub-divisions (sampling units) are called clusters iv. Stratified sampling * Sampling frame (the population) divided into homogenous classes/groups called strata according to one or more criteria (e. g. ex, age, job profiles * In each stratum, independent sampling (stratified random or stratified systematic) is undertaken * Optimal way to stratify is to find groups with large variability between strata; & very small variability within stratum 3. 3. Measures of central tendency: The arithmetic mean, mode, & median can be computed either: * From individual data values (ungrouped data); or * From data which have been tabulated in specific intervals (grouped) 3. 4. 1. 1. Calculation from ungrouped data vii. The mean viii.

A weighted arithmetic mean ix. Calculating arithmetic mean for large numbers x. The median 3. 4. 1. 2. 11. 1. Procedure to establish a median xi. The mode 3. 4. 1. 2. Calculation from grouped data set xii. The mean xiii. The median xiv. The mode 3. 4. Measures of variability (dispersion) 3. 5. 1. 3. The range 3. 5. 1. 4. The variance & standard variation 3. 5. 1. 5. Coefficient of variation Msambichaka, pp: 1-28 3. Data presentation 4. 5. Tabulations – principles: * Columns & row * Data alignment 4. 6. Graphics * Histograms * Charts

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