btarocket.blogg.se - Validity and reliability in quantitative research example

When an instrument of data collection used by the researcher yields a particular set of data, another researcher should be able to derive similar data using the same instrument. Hence, a social science researcher faces the challenging task of arriving at reliable and valid data and conclusions. It is known to us that knowledge claims in social science research are the plausible explanations. social phenomena, which is dynamic, fluidic, and difficult to predict, suffers from the inability of developing instruments to help researchers to make precise, accurate claims of knowledge. However, social sciences, because of its very nature of object of study, i.e.

What is important to note here is that natural sciences witnessed significant advancements in instrumentation which helped them to overcome the problems of reliability and validity. It is equally tough to decipher the underlying reasons for patterns of social relations as that of understanding natural phenomena by natural scientists. Social phenomena are complex and any attempt at understanding them is challenging. It has been a challenge to the social science researchers to claim the findings of their study as scientific as that of natural sciences. One of the most important concerns of social science researchers has been the issue of reliability and validity.

35. Academic Writing: Language, Presentation and Citation.

33. The Audience: Disciplinary peer group, sponsors and commonpublic.

32. Alternative sources/methods of knowledge/knowledge production.

31. Historical method in sociological research.

30. Computer Application in Qualitative Data Analysis.

28. Feminist Methodology in Sociological Research.

26. Theoretical Sampling, Saturation, and Grounded Theory.

25. Ethnography: Immersion in the Field and Thick Description.24. Exploring the Field – Research Cycles in Qualitative Approach.

23. Computer Application in Quantitative Data Analysis.

20. Processing and Analyzing Quantitative Data.

19. Non-probability Sampling: Principles and Procedures.

18. Probability Sampling: Principles and Procedures.

14. Research Methods 4: Testing Procedures.

10. Research questions and testing hypotheses.

8. The Problem of Objectivity and Value Neutrality.

7. Approaches to Data: Qualitative, Quantitative and Triangulation.

4. Taking stock of what is known: The use of library.

3. Types of Research and Designing Them.

2. Components of Social Research: Theory, Logic, and Method.

1. Methodology of Research in Sociology: A Historical Introduction.