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 :
- 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
- 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
- American Psychological Association (2020). "6.11". Publication Manual of the American Psychological Association: the official guide to APA style. American Psychological Association
- Tuomi, Ilkka (2000). "Data is more than knowledge". Journal of Management Information Systems. 6 (3): 103–117
- P. Beynon-Davies (2002). Information Systems: An introduction to informatics in organisations. Basingstoke, UK
- Nielsen, Sandro (2008). "The Effect of Lexicographical Information Costs on Dictionary Making and Use". Lexikos. 18: 170–189
- Stewart, Thomas (2001). Wealth of Knowledge. New York, NY: Doubleday.
- Liu, Alan (2004). The Laws of Cool: Knowledge Work and the Culture of Information. University of Chicago Press
- 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.
- 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 Association. 103 (10): 1339–1346
- Data Collection and Analysis By Dr. Roger Sapsford, Victor Jupp
- Ziafati Bafarasat, A. (2021) Collecting and validating data: A simple guide for researchers. Advance. Preprint
- Rudas, Tamas (2010). "Probability Theory: An Outline". In Lovric, Miodrag (ed.). International Encyclopedia of Statistical Science. Springer. pp. 1123–1126
- Williams, David (2001). "Preface". Weighing the Odds: A Course in Probability and Statistics. Cambridge University Press. pp. xi–xvii
- Hays, William Lee, (1973) Statistics for the Social Sciences, Holt, Rinehart and Winston, p. xii
- Dodge, Yadolah (2003). The Oxford Dictionary of Statistical Terms. Oxford University Press
- 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. 53: 20–27
- 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
- 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
- Mueller, I. (1969). "Euclid's Elements and the Axiomatic Method". The British Journal for the Philosophy of Science. 20 (4): 289–309
- 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
- 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)
- Woodward, W. A., Gray, H. L. & Elliott, A. C. (2012), Applied Time Series Analysis, CRC Press.
- 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
- M. R. Spiegel; S. Lipschutz; D. Spellman (2009). Vector Analysis. Schaum's Outlines (2nd ed.). US: McGraw Hill
- Rolfsen, Dale (1976). Knots and Links. Berkeley, California: Publish or Perish
- American College of Forensic Examiners Institute. (2016). The Certified Criminal Investigator Body of Knowledge. Boca Raton, Florida: CRC Press. pp. 112–113
- Dogan, Aysel (2005). "Confirmation of Scientific Hypotheses as Relations". Journal for General Philosophy of Science. 36 (2): 243–259
- Reiss, Julian; Sprenger, Jan (2020). "Scientific Objectivity". The Stanford Encyclopedia of Philosophy. Metaphysics Research Lab, Stanford University.
- Reid, Donald L. (2003). "Dr. Henry Faulds – Beith Commemorative Society". Journal of Forensic Identification. 53 (2)
- Tewari, RK; Ravikumar, KV (2000). "History and development of forensic science in India". J Postgrad Med. 46 (46): 303–308
- Keith Inman, Norah Rudin, Principles and Practice of Criminalistics: The Profession of Forensic Science (p. 32), CRC Press, 2000
- Creswell, J.W. (2012). Educational research: Planning, conducting, and evaluating quantitative and qualitative research. Upper Saddle River, NJ: Prentice Hall
- Bell, J. (1999). Doing your research project. Buckingham: OUP.
- Robson, C. (1993). Real-world research: A resource for social scientists and practitioner-researchers. Malden: Blackwell Publishing
- Porter, Roy; Lorraine Daston; Katharine Park. The Cambridge History of Science: Volume 3, Early Modern Science. p. 805
- McCrie, Robert D. "General Managerial Fundamentals and Competencies". Security Operations Management. 1st ed. Amsterdam: Butterworth-Heinemann/Elsevier, 2007. 93
- 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)
- 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.
- Schreiner, Wolfgang (2021). Thinking Programs: Logical Modeling and Reasoning About Languages, Data, Computations, and Executions. Springer Nature. p. 22
- 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
- Wheeler, Gregory R.; Pereira, Luís Moniz (2004). "Epistemology and Artificial Intelligence". Journal of Applied Logic. 2 (4): 469–493
- 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
- 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.