Dataset Analysis for Identifying General Data Statistics
Principal Investigator
Name
Jonathan Hubermann
Degrees
B.Eng
Institution
Concordia University
Position Title
Student
Email
About this CDAS Project
Study
PLCO
(Learn more about this study)
Project ID
PLCO-1119
Initial CDAS Request Approval
Dec 5, 2022
Title
Dataset Analysis for Identifying General Data Statistics
Summary
The project is for a data science course in which a unique dataset must be used to identify key trends and characteristics using data analysis tools in the engineering domain. Having been personally affected by Ovarian Cancer through a loved one, a dataset with information on biomarker results and diagnoses represents a unique and educational opportunity to learn more about the trends of this data and what correlations could be found between various attributes. This data will be studied for a short period of time and only final findings that reflect the entire dataset and not individual entires will be summarized and reported.
Aims
• To apply engineering database tools to analyze this dataset
• To identify key statistics among individual axes of data as well as correlations between different data attributes in the dataset
Collaborators
Jonathan Hubermann, Concordia University
Oliver Hassan, Concordia University
Nadia Beauregard, Concordia University
Eyal Azimov, Concordia University