Open Internet by MindsNet

Reviving Scientific Rigor in Data Science

The field of data science is facing a challenge in maintaining scientific rigor, particularly in hypothesis testing and validation. A recent PhD thesis highlights the erosion of scientific standards in data science research. This gap in rigorous research methods needs to be addressed to ensure the credibility and reliability of data science applications. Data scientists must revive and emphasize robust hypothesis testing and validation methods.

Computing & Technology, Information Technology, Data Science