Skip to main navigation
Skip to search
Skip to main content
Charles Sturt University Research Output Home
Home
Researchers
Research Organisations
Research Outputs
Datasets
Prizes
Activities
Press/Media
Impacts
Equipment
Search by expertise, name or affiliation
Scientific data analysis with R: Biostatistical applications
Azizur Rahman
, Faruq Abdulla, Md. Moyazzem Hossain
Gulbali Research Institute
Early Childhood Interdisciplinary Research Group
Computing, Mathematics and Engineering
Health Services Research Group
Imaging and Sensing Research Group
Cyber Security Research Group (CSRG)
Data Science and Engineering Research Unit
DaMRG - Data Mining Research Group
University of Canberra
Islamic University, Kushtia
RTM Al-Kabir Technical University
Cancer Care and Research Trust Bangladesh (CCRTB)
Jahangirnagar University
Newcastle University, United Kingdom
Research output
:
Book/Report
›
Book
1
Citation (Scopus)
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Scientific data analysis with R: Biostatistical applications'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Data Science
100%
Biostatistics
100%
Scientific Data Analysis
100%
Biological Health
66%
Medical Data
33%
Healthcare
33%
Statistical Analysis
33%
Industry Data
33%
Statistical Data
33%
Statistical Techniques
33%
Health Data
33%
Exponential Growth
33%
Practical Implementation
33%
Biological Data
33%
Complex Data
33%
Diverse Applications
33%
Statistical Knowledge
33%
Biological Datasets
33%
Medical Dataset
33%
R Language
33%
Data Science Technique
33%
Technology Convergence
33%
Combined Power
33%
Student Researchers
33%
Health Datasets
33%
Biological Industry
33%
Meaningful Knowledge
33%
Computer Science
Data Generation
100%
Scientific Data
100%
Open Source
100%
Exponential Growth
100%
Programming Language
100%
Mathematics
Biostatistics
100%
Exponential Growth
33%
Statistics
33%
Edge
33%
Statistical Analysis
33%
R Programming Language
33%