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Modern Concepts & Developments in Agronomy

Need for Shift from Hypothesis to Data Driven Approach in Fisheries Research- An Opinion Paper

  • Open or Close Shivakumar M*

    Professor of Aquatic Biology, College of Fisheries, India

    *Corresponding author:Shivakumar Magada, Professor of Aquatic Biology, College of Fisheries, India

Submission: January 06, 2019; Published: February 08, 2019

DOI: 10.31031/MCDA.2019.03.000571

ISSN: 2637-7659
Volume3 Issue5


Science is not changing every day, but our understanding. Through systematic research based on hypothesis, scientists give a lead towards possible truth. With more and more such hypothesis, we can go nearer to the truth. In all fields of research, it is customary to design research based on hypothesis. Scientists test their hypothesis using suitable test statistics and arrive at some conclusion. But the technical, economic feasibility and replicability of such results will decide the rate of its adoptability. The results of sample survey, hypothesis-based research may go wrong in many instances. Intricacies between parameters in a dynamic aquatic system are so complex. This leads us to conclude the results with certain assumptions and conditions. These conditions and assumptions limit the translation of knowledge into reality. When dealing with system level research, developing and under developed countries cannot afford to waste time and money on hypothesis. Due to the advancement information technology, huge data can be collected, processed which enabled better understanding of correlations between parameters and results can be predicted with precisely. If the research shifts from hypothesis to data driven approach, most of the results can directly applied in the intended field. The results of Data Driven Approach in Research (DDAR) will play vital role in designing developmental programs and policy making. DDAR also attracts funding support from industries and more technology will move to the field.

Keywords: Hypothesis; Data driven approach; Fisheries research; Big data

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