DocumentCode :
3660776
Title :
Extending R Boxplot Analysis to Big Data in Education
Author :
Rajiv Pandey;Nidhi Srivastava;Shahnaz Fatima
Author_Institution :
Amity Inst. of Inf. Technol., Amity Univ., Lucknow, India
fYear :
2015
fDate :
4/1/2015 12:00:00 AM
Firstpage :
1030
Lastpage :
1033
Abstract :
Big Data is the buzz word doing rounds in all areas of human existence be medical, social networks, research, it has also made inroads to education. The large size and complexity of datasets in Big Data need specialized statistical tools for analysis where R can come handy. This paper explores the analysis of Big Data in education using a contemporary statistical tool R. R provides multiple dimensions to statistical analysis of dataset, this paper however explores only the Box Plot feature to study the impact of outliers on the overall summary measure of the dataset. The feature of trimmed mean is incorporated to demonstrate its impact on outliers. The trimmed data set can be used in predictive analysis for a business intelligence prediction or educational context.
Keywords :
"Big data","Education","Data mining","Data analysis","Complexity theory","Indexes","Real-time systems"
Publisher :
ieee
Conference_Titel :
Communication Systems and Network Technologies (CSNT), 2015 Fifth International Conference on
Type :
conf
DOI :
10.1109/CSNT.2015.73
Filename :
7280075
Link To Document :
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