RESEARCH METHODS EXPECTATIONS OF A GRADUATE RECRUIT – KEFRI

							     RESEARCH METHODS:
 EXPECTATIONS OF A GRADUATE
 RECRUIT – KEFRI PERSPECTIVES

        Bernard N. Kigomo
(Kenya Forestry Research Institute)

 Discussion paper for “Teaching Research
       Methods Workshop”, ICRAF,
              31st May 2005
                                           1
         Introduction

Forest owners, state, individuals or
private must admit an aim to achieve
more or pay less (= use less resources)
or both. Their aim is maximum yields or
greatest benefits, usually at the “lowest
possible” cost. The ultimate focus is
eventually to enforce efficiency of
production of goods and benefits, with
severe controls on use of resources.
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To maximize on the above interest by a
forest owner, research aimed at
improving efficiency and gains is
therefore necessary. Research methods
are integral part of a research process.
Research and experiments are a
continuously necessary instruments of
such investments, management and
policy. Hence, research is an obligatory
part of the activities of public servants
and commercial employees.
                                        3
It is necessary, therefore, that existing
education system recognize the need to
provide knowledge in research methods
to its students within its curriculum
implementation. To support forestry
development and, therefore, enhance
improvement in outputs by forest
owners and farmers owning trees,
young forestry graduates should be
basically equipped with the following
research methodology elements:

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    Required basic knowledge
      on Research Methods
• Purpose of research and available approaches
  and opportunities
• Defining objectives and translating objectives to
  questions ie. problem analysis
• Sampling methods
  - Defining population
  - Selection of treatments/assessments
  - Plot/sample shape and size
  - The art of replications and randomization
  - The art of stratification                      5
     Experiment/Study designs and rationales

-     Latin square
-     Randomized
-     Randomized block
-     Factorial designs
-     Stratification
-     Stratified random
-     Stratified random block
-     Questionnaire

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     Plot/Sample Assessment
- Choice of parameters
- Defining variables and attributes to be
  counted or measured
- Staff training
- Tools of assessments
- Practical exposure on use of
   assessment tools
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         •     Recording of results

-   Field design maps
-   Location maps
-   Record forms designs
-   Field data booking orientation



                                      8
        Planning for analysis

- Defining hypothesis and their
  alternatives
- Understanding methods of analysis
- Understand program(s) available/
  relevant for computation

                                      9
    Basic statistical knowledge
- Statistics of normal distribution
- Difference between means of small samples
  (tests)
- Differences between means of two sets of
  paired observations
- Handling parametric and non-parametric
   data/results
- Treatment of percentages, counts or
  proportions
- The art of treating missing data/records    10
- Statistics of the normal distribution and
     sampling error from random samples
-   Handling stratified random block sampling
    data
-   Analysis of variance for different
     classification/designs
-    Partitioning treatments
-    Linear regression and correlation
-    Chi-squared test of conformity with a
     hypothesis

• The basics of data entry and management
  using computer soft wares.
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