Refining the concept of scientific inference when working with big data : proceedings of a workshop--in brief / Ben A. Wender.

Format:

Book

Author/Creator:

Wender, Ben A., author.

Series:

Workshop in brief.

Workshop in brief

Language:

English

Subjects (All):

Inference.

Big data.

Physical Description:

1 online resource (4 pages) : illustrations.

Other Title:

Refining the concept of scientific inference when working with big data

Place of Publication:

Washington (DC) : National Academies Press, 2016.

Summary:

Big Data--broadly considered as datasets whose size, complexity, and heterogeneity preclude conventional approaches to storage and analysis--continues to generate interest across many scientific domains in both the public and private sectors. However, analyses of large heterogeneous datasets can suffer from unidentified bias, misleading correlations, and increased risk of false positives. In order for the proliferation of data to produce new scientific discoveries, it is essential that the statistical models used for analysis support reliable, reproducible inference. The National Academies of Sciences, Engineering, and Medicine convened a workshop to discuss how scientific inference should be applied when working with large, complex datasets.

Notes:

Description based on publisher supplied metadata and other sources.