Data analysis


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Data analysis

  2. 2. QUALITATIVE DATAOpen-endedquestionsTestimonialsIndividualinterviewsDiscussiongrps/focus grpinterviewsLogs, journalsand diariesObservationsDocuments, reports, newsarticlesStories Case studies
  3. 3. What is CONTENT ANALYSIS?0 Method used to collect and analyse data.0 A technique that enables researchers to study humanbehaviour through analysis of their communication.0 A methodology that is often used in conjunction withother methods; historical and ethnographic research.
  4. 4. APPLICATIONSDescribe trendsUnderstand organizational patternsInfer attitudes, values, cultural patternsCompareGive researchers insights into problems/hypotheses
  5. 5. CATEGORIZATION• Determines categories beforeanalysis begins1 – Presetcategories• Become familiar with thedescriptive informationcollected• And allows the categories toemerge2 Emergentcategories
  6. 6. STEPS IN CONTENTANALYSISDetermineobjectivesDefineTermsSpecify theUnit ofAnalysisLocateRelevantDataDevelop aRationaleDevelop aSamplingPlanFormulateCodingCategoriesCheckReliability& ValidityAnalyseData
  7. 7. 1. Determine Objectives0 Some reasons to do content analysis:0 To obtain descriptive information about a topic0 To formulate themes0 To check other research findings0 To obtain information useful in dealing witheducational problems0 To test hypotheses
  8. 8. 2. Define Terms0 To avoid frustrations, terms need to be clearly definedbeforehand or as the research progresses.3. Specify Unit of Analysis0 Be sure of the unit that is being analysed – what isanalysed; words? Sentences? Phrases?
  9. 9. 4. Locate Relevant Data0 Locate the relevant data that will be analysed whichare relevant to the OBJECTIVES.0 The relationship between the content to be analysedand the objectives should be clear.0 HOW TO ENSURE THIS?HAVE A SPECIFIC RESEARCH QUESTION (ANDPOSSIBLY A HYPOTHESIS)
  10. 10. 5. Develop a Rationale0 A conceptual link is required to explain how the dataare related to the objectives.0 Sometimes, the link between question and contentcan be obviously seen. E. g. A study on bias inadvertisement  study the contents of newspaper &magazine advertisements.
  11. 11. 0 However, it may not always be the case. E. g. A study onchanges in perception towards police officers  study theway they are portrayed in short stories in magazinepublished at different times.0 Content analysis – use available materials.0 To generate own data – use OPEN-ENDED QUESTIONS.0 Then the data will be analysed.
  12. 12. 6. Develop a Sampling Plan0 Any form of communication may be sampled at anyconceptual level that is appropriate.0 Example: Television programmes may be sampled bytype, channel, sponsor, producer, or time of dayshown.
  13. 13. Examples of SamplingDesignsPurposive SamplingDesignSelect only thesamples whichresearcher find havespecific purpose forthe researchThis relies on theresearcher’sprevious knowledgeRandomSamplingEach & everymember of thepopulation has anequal andindependent chanceof being selected
  14. 14. 0 Cluster Sampling• The researcher divides the entiresubjects into different subgroups.• And then randomly selects the finalsubjects proportionally from differentstrata. ( )StratifiedSampling• The entire population is divided into groups,or clusters and a random sample, of theseclusters are selected.• All observations in the selected clusters areincluded in this sample. (
  15. 15. 7. Formulate CodingCategories0 Formulate categories that are relevant to theinvestigation.0 Categories should be EXPLICIT that other researchercould use them.0 Categories developed often emerge from the date.0 It is a complex process.
  16. 16. Manifest Content (MC) vs. LatentContent (LC)0 MC content of a communication refers to the obvious,surface content;0 They are directly accessible.0 No inferences or underlying meaning are necessary.0 ADVANTAGE  Easier coding and reliability0 DISADVANTAGE  ValidityWORDS, PICTURES, IMAGES ETC
  17. 17. 0 LC refers to the meaning underlying what is said or shown.0 Example; a researcher might read through the entireoutline or sample of pages.0 From there the researcher will make an overall assessmentof the degree of a certain aspect they’ve analysed.0 ADVANTAGE  Getting the underlying meaning0 DISADVANTAGE  ReliabilityCLASSROOM ACTIVITIES,HOMEWORK ASSIGNMENTS
  18. 18. Which one to use?BOTH–Wheneverpossible
  19. 19. 8. Check Reliability &Validity0 How to check RELIABILITY?Selecting second sample of materials ordividing the original sample in half.
  20. 20. 0 How to check VALIDITY?Check MC against LC and compareeither or both with results fromdifferent instruments.
  21. 21. 9. Analyse Data0 The end product of the coding process MUST BE NUMBERS.0 Common ways of doing this are by recording:0 the frequencies of a particular incident or item and0 the proportion of particular occurrences to totaloccurrences0 Developing themes based on the particular coding from thestudy.0 Using computer analysis to interpret coded data, or todevelop the initial categories used in the analysis.0
  22. 22. Column 1 – List of newspapers by numbersColumn 2 – List of locationColumn 3 – List of circulationColumn 4 – Number of editorials coded for each paperColumn 5 – Subjective assessment by the researcher of each newspaper’seditorial policyColumn 6 & 7 – Record the number of certain types of editorials
  23. 23. Illustration of ContentAnalysisAn analysis of all the research studiespublished in Theory and Research in SocialEducation (TRSE), 1979 – 1986.
  24. 24. The Analysing Process0 Read the studies that was published during the periodthat fell in ONE of these categories.0 To test their agreement  They read the same studies& categorized them. After that, they compared.0 They had almost similar categories & added somesubcategories and new categories.
  25. 25. FINAL SET OFCATEGORIES (pg.487)• They reread theinitial six &remaining 40 usingthe new categories.• Sat down &compared theirassessments.• Although therewere somedisagreements,they finally came toan agreement withthe assessments.
  26. 26. Using Computer Analysis0 Word processing programmes; using the ‘find’ command.0 Examples of qualitative computer programmes; ATLAS.ti,QSR, NUD*IST, Nvivo and HyperResearch.0 They identify words, phrases, sentences, tabulate theiroccurrences, print and tabulate graphs and sort andregroup words, phrases, sentences according to how they fitin a particular set of categories.
  27. 27. Example of Qualitative DataAnalysis0
  28. 28. An overview
  29. 29. The Method
  30. 30. Categories of Content0 Violent behavior was further divided into one ofseveral subcategories:
  31. 31. The Results0 Overview of findings
  32. 32. Advantages & DisadvantagesADVANTAGES DIASADVANTAGES It is UNOBTRUSIVE  Limited to recorded information Useful in analysing INTERVIEW& OBSERVATIONAL DATA Establishing validity Can delve into records anddocuments Researchers have the tendency tosay that interpretations gleanedfrom a particular contentanalysis indicate the causes of aphenomenon Simple and economical logistics Data are readily available & canbe returned to if necessary replication of study