Collecting, analyzing and interpreting dataPresentation Transcript
Collecting the data This is the stage where appropriateinformation for answering the research question is collected.
The researcher should selectthe most appropriate methods of collecting data and the required data collection tools.
This calls for consideration of the nature of the investigation,the respondents, objectives and scope of the inquiry, resources available, time and the desired degree of accuracy.
Analysis and interpretation of data Analysis of data involves the application of raw data into categories through coding and tabulation.
The unwieldy data is condensed into manageable categories for further analysis.
The researcher attempts toclassify the raw data into some purposeful and usable categories.
In coding, the categories of data are transformed into symbols that may be tabulated and counted.
Use of computers is helpfulespecially when dealing with large amounts of data
Analysis work after tabulation isusually based on computation of various statistical measures.
Data entry and analysissoftware such as SPSS, Excel and Access are helpful at this stage.
In analysis, relationships or differences that support orconflict the original hypothesis are subjected to tests of significance to determine thevalidity with which conclusions can be made
If there are no hypotheses, theresearcher seeks to explain the findings.
Handling, Organizing andAnalyzing Qualitative Data
Qualitative data comes in different shapes and forms: focus group interview transcripts, notesscribbled down during interviews or participant observation, text of newspaper articles, transcripts of television or radio programmes.
The analysis of qualitative data is very much a matter ofdiscovering what occurs where, in which context, discussed inwhich terms, using what terms, themes or key words.
The thinking, judging, deciding, interpreting, etc., are more or less done by the researcher.
The nature of data quantitative [numbers] vs.qualitative [words, themes, etc.]
Analysis is really all aboutabstracting from your data what you consider important and significance in answering your research questions.