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APPROACHES TO RESEARCH

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approaches to research quan: numerical data analyzed by statistical methods qual: nonnumerical data, nonstatistical method mix: combination of quan-quan – PowerPoint PPT presentation

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Title: APPROACHES TO RESEARCH


1
APPROACHES TO RESEARCH
  • QUAN NUMERICAL DATA ANALYZED BY STATISTICAL
    METHODS
  • QUAL NONNUMERICAL DATA, NONSTATISTICAL METHOD
  • MIX COMBINATION OF QUAN-QUAN

2
QUAN
  • DEFINE VARIABLES IN ADVANCE
  • ASSIGN LOGICAL VALUES TO THE VARIABLE
  • EXPRESS THE VALUES IN NUMBERS
  • Regard sample-related variation as a problem to
    fix by drawing a large sample and rely on the
    commonalities of the sample
  • Follow meaning in general strategy
  • Predeterrmined numerical category system

3
Qual
  • Use coding but verbal, short textual label
  • Coding is not decided apriori, but left open and
    flexible
  • Average description will omit individual stories
  • Real meaning lies with individual cases
  • Believe that there are multiple meanings to
    discover
  • In depth understanding meaning in particular
  • Emergent, flexibel coding

4
Quan
  • Using larger sample
  • Relying on formalized system of statistics
  • Highly regulated way of achieving
    macro-perspective

5
Qual
  • Focusing on aunique meaning carried out
    byindividual organism
  • Relying on researchers individual sensitivity
  • Flexible and higly context-sensitive

6
3 position
  • Purist quan-qual are mutually exlusive
  • Situationalist use macro and micro level of
    analysis. Demotivation is for qualitative,
    language globalization is for quantitative both
    approaches have value if they are applied
    appropriately (either/or)
  • Pragmatist integration of quan-qual. Look at the
    same research qiestion from different angles,
    using the other approach

7
Quantitative
  • Using numbers powerful, but weak without
    contexts
  • Apriori categorization categories and valued are
    decided prior to the actual study
  • Variable rather than cases
  • Statistics and the language of statistics
  • Standardized procedures to assess objective
    reality that is out there independent of
    researchers subjective perception
  • Quest for generality and universal law e.g.
    Quick count
  • Strengths systematic, focused, tightly
    controlled, , realible and replicable data, quick
    and offer good value for money, high reputation.

8
QUALITATIVE
  • Emergent research design
  • Use various types of data recorded interview,
    journal, diary entries, document and images
  • Takes place in natural setting
  • Concerned with subjective opinion, experiences
  • Small sample size
  • Interpretive analysis

9
Strengths of Qual
  • Exploratory nature
  • Making sense of complexity
  • Answering why questions
  • Broadening our understanding (possible
    interpretaion)
  • Longitudinal observation of dynamic phenomena
  • Flexibility when things go wrong
  • Rich material for research reports

10
Weakness of Qual
  • Sample size and generalizability
  • Researchers role
  • Lack of methodological rigor
  • Time consuming
  • Too complex or too narrow theories
  • Labour intensive
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