SCAD: Scalable Computing and Algorithms for Digital Health
HPI-SCAD-C Concepts and Methods
SCAD: Scalable Computing and Algorithms for Digital Health
HPI-SCAD-T Technologies and Tools
SCAD: Scalable Computing and Algorithms for Digital Health
HPI-SCAD-S Specialization
DICR: Digitalization of Clinical and Research Processes
HPI-DICR-C Concepts and Methods
DICR: Digitalization of Clinical and Research Processes
HPI-DICR-T Technologies and Tools
DICR: Digitalization of Clinical and Research Processes
HPI-DICR-S Specialization
APAD: Acquisition, Processing and Analysis of Health Data
HPI-APAD-C Concepts and Methods
APAD: Acquisition, Processing and Analysis of Health Data
HPI-APAD-T Technologies and Tools
APAD: Acquisition, Processing and Analysis of Health Data
HPI-APAD-S Specialization
Data Engineering MA
DATA: Data Analytics
HPI-DATA-T Techniken und Werkzeuge
DATA: Data Analytics
HPI-DATA-S Spezialisierung
PREP: Data Preparation
HPI-PREP-K Konzepte und Methoden
PREP: Data Preparation
HPI-PREP-T Techniken und Werkzeuge
PREP: Data Preparation
HPI-PREP-S Spezialisierung
DATA: Data Analytics
HPI-DATA-K Konzepte und Methoden
IT-Systems Engineering MA
OSIS: Operating Systems & Information Systems Technology
HPI-OSIS-K Konzepte und Methoden
OSIS: Operating Systems & Information Systems Technology
HPI-OSIS-T Techniken und Werkzeuge
IT-Systems Engineering
HPI-ITSE-A Analyse
Description
This course introduces basic concepts of statistical data analysis and their practical application in mobile computing.
The course covers the entire range of statistical data analysis. Topics include how to design an empirical data collection in a statistical valid way, how to collect data from daily life with the help of mobile computing, and how to achieve statistical test results.
Lessons learned will be applied in practice by conducting empirical experiments with mobile phones.
There are no special requirements to attend this lecture since all needed background knowledge is provided within the course.
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