Differentiating Strong Data and Evidence from Weak Data and Evidence: Another Heuristic for use in General and Social Sciences Research


Authors : Sujay Rao Mandavilli

Volume/Issue : Volume 10 - 2025, Issue 6 - June


Google Scholar : https://tinyurl.com/48n7p6yc

DOI : https://doi.org/10.38124/ijisrt/25jun1831

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Note : Google Scholar may take 30 to 40 days to display the article.


Abstract : This paper is as usual tied to many of our earlier papers in the business. The core objective of this paper is to show why techniques to isolate and differentiate strong evidence from weak evidence need to be formulated, orchestrated and developed and communicated to the wider public and masses, and why this is in the best interest of science and society i.e. why it has the potential to catapult science and scientific temper to an altogether higher league and trajectory in many different parts of the world. We begin this paper by reviewing what data is, and examine the different types of data in common and widespread use. The different types of evidence are also critically and thoroughly examined, and the differences between data, information and evidence suitably brought out. The importance of data collection, data evaluation and examination data modeling, data correlation, and data synthesis are also brought out, and the importance of strong methods in this regard duly stressed and emphasized. A host and plethora of related mathematical and statistical techniques are also probed and investigated as they add meat and substance to the paper. The importance of research design is also emphasized, and different types of research design are probed and investigated. All the concepts in this paper are linked in a continuous chain, and the essential requirements of rock solid and high-quality research laid bare. While also providing suitable examples to bolster our case, we stress and emphasize the need to rank and rate different aspects of scientific activity on the basis of their inherent strengths. As such, we expect this paper to be a crucial cog in the wheel of our globalization of science movement.

References :

  1. P. Checkland and S. Holwell (1998). Information, Systems, and Information Systems: Making Sense of the Field. Chichester, West Sussex: John Wiley & Sons. pp. 86–89
  2. Vines, Timothy H.; Albert, Arianne Y. K.; Andrew, Rose L.; Débarre, Florence; Bock, Dan G.; Franklin, Michelle T.; Gilbert, Kimberly J.; Moore, Jean-Sébastien; Renaut, Sébastien; Rennison, Diana J. (2014-01-06). "The availability of research data declines rapidly with article age". Current Biology. 24 (1): 94–97
  3. American Psychological Association (2020). "6.11". Publication Manual of the American Psychological Association: the official guide to APA style. American Psychological Association
  4. Tuomi, Ilkka (2000). "Data is more than knowledge". Journal of Management Information Systems6 (3): 103–117
  5. P. Beynon-Davies (2002). Information Systems: An introduction to informatics in organisations. Basingstoke, UK
  6. Nielsen, Sandro (2008). "The Effect of Lexicographical Information Costs on Dictionary Making and Use". Lexikos18: 170–189
  7. Stewart, Thomas (2001). Wealth of Knowledge. New York, NY: Doubleday.
  8. Liu, Alan (2004). The Laws of Cool: Knowledge Work and the Culture of InformationUniversity of Chicago Press
  9. Floridi, Luciano (2005). "Semantic Conceptions of Information". In Zalta, Edward N. (ed.). The Stanford Encyclopedia of Philosophy (Winter 2005 ed.). Metaphysics Research Lab, Stanford University.
  1. Most, Marlene M.; Craddick, Shirley; Crawford, Staci; Redican, Susan; Rhodes, Donna; Rukenbrod, Fran; Laws, Reesa (October 2003). "Dietary quality assurance processes of the DASH-Sodium controlled diet study". Journal of the American Dietetic Association103 (10): 1339–1346
  2. Data Collection and Analysis By Dr. Roger Sapsford, Victor Jupp
  3. Ziafati Bafarasat, A. (2021) Collecting and validating data: A simple guide for researchers. Advance. Preprint
  4. Rudas, Tamas (2010). "Probability Theory: An Outline". In Lovric, Miodrag (ed.). International Encyclopedia of Statistical Science. Springer. pp. 1123–1126
  5. Williams, David (2001). "Preface". Weighing the Odds: A Course in Probability and Statistics. Cambridge University Press. pp. xi–xvii
  6. Hays, William Lee, (1973) Statistics for the Social Sciences, Holt, Rinehart and Winston, p. xii
  7. Dodge, Yadolah (2003). The Oxford Dictionary of Statistical Terms. Oxford University Press
  8. Ginammi, Michele (February 2016). "Avoiding reification: Heuristic effectiveness of mathematics and the prediction of the Ω particle". Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics. 5320–27
  9. Wilson, Edwin B.; Lewis, Gilbert N. (November 1912). "The Space-Time Manifold of Relativity. The Non-Euclidean Geometry of Mechanics and Electromagnetics". Proceedings of the American Academy of Arts and Sciences. 48 (11): 389–507
  10. Rossi, Richard J. (2006). Theorems, Corollaries, Lemmas, and Methods of Proof. Pure and Applied Mathematics: A Wiley Series of Texts, Monographs and Tracts. John Wiley & Sons. pp. 1–14, 47–48
  11. Mueller, I. (1969). "Euclid's Elements and the Axiomatic Method". The British Journal for the Philosophy of Science20 (4): 289–309
  12. De Gooijer, Jan G.; Hyndman, Rob J. (2006). "25 Years of Time Series Forecasting". International Journal of Forecasting. Twenty Five Years of Forecasting. 22 (3): 443–473
  13. Weigend A. S., Gershenfeld N. A. (Eds.) (1994), Time Series Prediction: Forecasting the Future and Understanding the Past. Proceedings of the NATO Advanced Research Workshop on Comparative Time Series Analysis (Santa Fe, May 1992)
  14. Woodward, W. A., Gray, H. L. & Elliott, A. C. (2012), Applied Time Series AnalysisCRC Press.
  15. Shumway R. H., Stoffer D. S. (2017), Time Series Analysis and its Applications: With R Examples (ed. 4), Springer, ISBN 978-3-319-52451-1
  16. M. R. Spiegel; S. Lipschutz; D. Spellman (2009). Vector Analysis. Schaum's Outlines (2nd ed.). US: McGraw Hill
  17. Rolfsen, Dale (1976). Knots and Links. Berkeley, California: Publish or Perish
  18. American College of Forensic Examiners Institute. (2016). The Certified Criminal Investigator Body of Knowledge. Boca Raton, Florida: CRC Press. pp. 112–113
  19. Dogan, Aysel (2005). "Confirmation of Scientific Hypotheses as Relations". Journal for General Philosophy of Science. 36 (2): 243–259
  20. Reiss, Julian; Sprenger, Jan (2020). "Scientific Objectivity". The Stanford Encyclopedia of Philosophy. Metaphysics Research Lab, Stanford University.
  21. Reid, Donald L. (2003). "Dr. Henry Faulds – Beith Commemorative Society". Journal of Forensic Identification53 (2)
  22. Tewari, RK; Ravikumar, KV (2000). "History and development of forensic science in India". J Postgrad Med46 (46): 303–308
  23. Keith Inman, Norah Rudin, Principles and Practice of Criminalistics: The Profession of Forensic Science (p. 32), CRC Press, 2000
  24. Creswell, J.W. (2012). Educational research: Planning, conducting, and evaluating quantitative and qualitative research. Upper Saddle River, NJ: Prentice Hall
  25. Bell, J. (1999). Doing your research project. Buckingham: OUP.
  26. Robson, C. (1993). Real-world research: A resource for social scientists and practitioner-researchers. Malden: Blackwell Publishing
  27. Porter, Roy; Lorraine Daston; Katharine Park. The Cambridge History of Science: Volume 3, Early Modern Science. p. 805
  28. McCrie, Robert D. "General Managerial Fundamentals and Competencies". Security Operations Management. 1st ed. Amsterdam: Butterworth-Heinemann/Elsevier, 2007. 93
  29. Reid, Donald L. (2003). "Dr. Henry Faulds – Beith Commemorative Society". Journal of Forensic Identification. 53 (2). See also this on-line article on Henry Faulds: Tredoux, Gavan (December 2003)
  30. Rocci, Andrea (8 March 2017). Modality in Argumentation: A Semantic Investigation of the Role of Modalities in the Structure of Arguments with an Application to Italian Modal Expressions. Springer. p. 26.
  31. Schreiner, Wolfgang (2021). Thinking Programs: Logical Modeling and Reasoning About Languages, Data, Computations, and Executions. Springer Nature. p. 22
  32. Sharpe, Matthew (2018). "The Demise of Grand Narratives? Postmodernism, Power-knowledge, and Applied Epistemology". In Coady, David; Chase, James (eds.). The Routledge Handbook of Applied Epistemology. Routledge. pp. 318–331
  33. Wheeler, Gregory R.; Pereira, Luís Moniz (2004). "Epistemology and Artificial Intelligence". Journal of Applied Logic2 (4): 469–493
  34. Advocating output criteria based scientific and research methodologies: Why the reliability of scientific and research methods must be measured based on output criteria and attributes Sujay Rao Mandavilli IJISRT, August 2023
  35. Recognizing “Non self-cancelling contradictory evidence” as and when it occurs or arises: Delineating its special place in twenty-first scientific method Sujay Rao Mandavilli, IJISRT, January 2025

This paper is as usual tied to many of our earlier papers in the business. The core objective of this paper is to show why techniques to isolate and differentiate strong evidence from weak evidence need to be formulated, orchestrated and developed and communicated to the wider public and masses, and why this is in the best interest of science and society i.e. why it has the potential to catapult science and scientific temper to an altogether higher league and trajectory in many different parts of the world. We begin this paper by reviewing what data is, and examine the different types of data in common and widespread use. The different types of evidence are also critically and thoroughly examined, and the differences between data, information and evidence suitably brought out. The importance of data collection, data evaluation and examination data modeling, data correlation, and data synthesis are also brought out, and the importance of strong methods in this regard duly stressed and emphasized. A host and plethora of related mathematical and statistical techniques are also probed and investigated as they add meat and substance to the paper. The importance of research design is also emphasized, and different types of research design are probed and investigated. All the concepts in this paper are linked in a continuous chain, and the essential requirements of rock solid and high-quality research laid bare. While also providing suitable examples to bolster our case, we stress and emphasize the need to rank and rate different aspects of scientific activity on the basis of their inherent strengths. As such, we expect this paper to be a crucial cog in the wheel of our globalization of science movement.

CALL FOR PAPERS


Paper Submission Last Date
31 - July - 2025

Video Explanation for Published paper

Never miss an update from Papermashup

Get notified about the latest tutorials and downloads.

Subscribe by Email

Get alerts directly into your inbox after each post and stay updated.
Subscribe
OR

Subscribe by RSS

Add our RSS to your feedreader to get regular updates from us.
Subscribe