Big Data in Psychology
Big Data in Psychology
  • Big Data in Psychology
  • Big Data in Psychology

Big Data in Psychology

Methods and Applications

herausgegeben von: Mike W.-L. Cheung, Suzanne Jak

Reihe: Zeitschrift für Psychologie - Band 38

Sind Sie bereits Abonnent dieser Buchreihe?
Meine Abos

In Ihrem Kundenkonto können Sie im Bereich "Meine Abos" Ihre bereits bestehenden Abonnements registrieren. Bei Reihen mit reduzierten Abonnenten-Preisen erhalten Sie diese anschließend automatisch im Shop.

Buch
Buchreihe
Buch
Big Data in Psychology
ISBN: 9780889375512
2018, iv/80 Seiten
34,95 €
inkl. USt.
merken
Buchreihe
Artikelnummer: BV-ZP Methods and Applications
Abrechnung je Ausgabe
Band 3
Verfügbar als:
Band 4
Verfügbar als:
Band 5
Verfügbar als:
Band 6
Verfügbar als:
Band 7
Verfügbar als:
Band 8
Verfügbar als:
Band 9
Verfügbar als:
Band 12
Verfügbar als:
Band 15
Verfügbar als:
Band 16
Verfügbar als:
Band 17
Verfügbar als:
Band 18
Verfügbar als:
Band 20
Verfügbar als:
Band 21
Verfügbar als:
Band 22
Verfügbar als:
Band 24
Verfügbar als:
Band 25
Verfügbar als:
Band 26
Verfügbar als:
Band 27
Verfügbar als:
Band 29
Verfügbar als:
Band 30
Verfügbar als:
Band 31
Verfügbar als:
Band 32
Verfügbar als:
Band 33
Verfügbar als:
Band 35
Verfügbar als:
Band 36
Verfügbar als:
Band 37
Verfügbar als:
Band 39
Verfügbar als:
Band 40
Verfügbar als:
Band 42
Verfügbar als:
Band 43
Verfügbar als:
Band 45
Verfügbar als:
Band 47
Verfügbar als:
Band 48
Verfügbar als:
Band 49
Verfügbar als:
Band 50
Verfügbar als:
Big Data in Psychology
Big Data in Psychology
  • Big Data in Psychology
  • Big Data in Psychology

Big data is becoming more prevalent in psychology and the behavioral sciences, and so are the methodological and statistical issues that arise from its use. Psychologists need to be equipped to deal with these. Big data can be generated in experimental studies where, for example, participants’ physiological and psychological responses are tracked over time or where human brain imaging is employed. Observational data from websites such as Facebook, Twitter, and Google is also of increasing interest to psychologists. These sometimes huge data sets, which are often too large for standard computers and can also contain multiple types of data, bring with them challenging questions about data quality and the generalizability of the results as well as which statistical tools are suitable for analyzing them.

The contributions in this volume explore these challenges, looking at the potential of applying machine learning techniques to big data in psychology as well as the split/analyze/meta-analyze (SAM) approach, which allows big data to be split up into smaller datasets so they can be analyzed with conventional multivariate techniques on standard computers. The issues of replicability, prediction accuracy, and combining types of data are also investigated.

To the online journal

Ref-ID:600551_M P-ID:600551_M

Artikel Hinzugefügt