Abstract
Data science describes the process of asking questions, analyzing, and manipulating large data sets in the search for patterns and knowledge by using diverse mathematical models and methods (Sullivan, 2018). With the great advances of technology and computer science, scientists now have quick access to large amounts of data from a variety of sources. These sources are digitilized and can be monetary as in credit card/banking information or even the most personal from Electronic Medical Records. Concurrently there has been increased capacity to store and retrieve these huge amounts of data electronically. The speed of delivering all this data by electronic transmission is something never experienced before. This speed coupled with organization and labeling of the data within software programs makes it easy to use the data for different analyses.
Sigma Membership
Gamma Kappa
Lead Author Affiliation
The State University of New York at Buffalo, Buffalo, New York, USA
Type
Poster
Format Type
Text-based Document
Study Design/Type
N/A
Research Approach
N/A
Keywords:
Data Science, Health Care, Nursing Research, Research
Recommended Citation
Pasek, Lana, "Learning to do data science healthcare research" (2019). Convention. 51.
https://www.sigmarepository.org/convention/2019/posters_2019/51
Conference Name
45th Biennial Convention
Conference Host
Sigma Theta Tau International
Conference Location
Washington, DC, USA
Conference Year
2019
Rights Holder
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All permission requests should be directed accordingly and not to the Sigma Repository.
All submitting authors or publishers have affirmed that when using material in their work where they do not own copyright, they have obtained permission of the copyright holder prior to submission and the rights holder has been acknowledged as necessary.
Acquisition
Proxy-submission
Learning to do data science healthcare research
Washington, DC, USA
Data science describes the process of asking questions, analyzing, and manipulating large data sets in the search for patterns and knowledge by using diverse mathematical models and methods (Sullivan, 2018). With the great advances of technology and computer science, scientists now have quick access to large amounts of data from a variety of sources. These sources are digitilized and can be monetary as in credit card/banking information or even the most personal from Electronic Medical Records. Concurrently there has been increased capacity to store and retrieve these huge amounts of data electronically. The speed of delivering all this data by electronic transmission is something never experienced before. This speed coupled with organization and labeling of the data within software programs makes it easy to use the data for different analyses.
Description
45th Biennial Convention 2019 Theme: Connect. Collaborate. Catalyze.