Synphne accelerated stroke rehabilitation system : data analytics and cloud computing (Business Data)
This final year project involved the analyzing and interpreting data using Microsoft Excel and R Studio. Visualizations of data were achieved in R Studio if Microsoft Excel was unable to. Several real live examples by Amazon, Target, Wal-Mart, BP and many more were explained with the companies usin...
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sg-ntu-dr.10356-722132023-03-04T18:45:55Z Synphne accelerated stroke rehabilitation system : data analytics and cloud computing (Business Data) Sufyan Mohamad Ali Heng Kok Hui, John Gerard School of Mechanical and Aerospace Engineering SynPhNe Pte Ltd DRNTU::Engineering::Mechanical engineering This final year project involved the analyzing and interpreting data using Microsoft Excel and R Studio. Visualizations of data were achieved in R Studio if Microsoft Excel was unable to. Several real live examples by Amazon, Target, Wal-Mart, BP and many more were explained with the companies using Big Data to improve their profit and productivity. Online courses to learn the R language, R Studio and Data Analysis were required for the completion of this project. R Studio was used to analyze and visualize the data. Microsoft Excel was used to rearrange the data. There were 7 steps in the data analysis. Data was retrieved from the Big City Health Coalition. 5 indicators from the Chronic Diseases section were analyzed. Histogram was used to find the highest count of values for the required settings. Scatterplot matrix with linear regression was used to have an overview of which variable have associations with which. A linear regression equation was acquired upon comparing the associated variables. In the end, using analytic tools and steps, it is possible to obtain critical metrics. Bachelor of Engineering (Mechanical Engineering) 2017-05-30T02:50:28Z 2017-05-30T02:50:28Z 2017 Final Year Project (FYP) http://hdl.handle.net/10356/72213 en Nanyang Technological University 57 p. application/pdf |
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DRNTU::Engineering::Mechanical engineering Sufyan Mohamad Ali Synphne accelerated stroke rehabilitation system : data analytics and cloud computing (Business Data) |
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This final year project involved the analyzing and interpreting data using Microsoft Excel and R Studio. Visualizations of data were achieved in R Studio if Microsoft Excel was unable to.
Several real live examples by Amazon, Target, Wal-Mart, BP and many more were explained with the companies using Big Data to improve their profit and productivity.
Online courses to learn the R language, R Studio and Data Analysis were required for the completion of this project. R Studio was used to analyze and visualize the data. Microsoft Excel was used to rearrange the data.
There were 7 steps in the data analysis. Data was retrieved from the Big City Health Coalition. 5 indicators from the Chronic Diseases section were analyzed. Histogram was used to find the highest count of values for the required settings. Scatterplot matrix with linear regression was used to have an overview of which variable have associations with which. A linear regression equation was acquired upon comparing the associated variables.
In the end, using analytic tools and steps, it is possible to obtain critical metrics. |
author2 |
Heng Kok Hui, John Gerard |
author_facet |
Heng Kok Hui, John Gerard Sufyan Mohamad Ali |
format |
Final Year Project |
author |
Sufyan Mohamad Ali |
author_sort |
Sufyan Mohamad Ali |
title |
Synphne accelerated stroke rehabilitation system : data analytics and cloud computing (Business Data) |
title_short |
Synphne accelerated stroke rehabilitation system : data analytics and cloud computing (Business Data) |
title_full |
Synphne accelerated stroke rehabilitation system : data analytics and cloud computing (Business Data) |
title_fullStr |
Synphne accelerated stroke rehabilitation system : data analytics and cloud computing (Business Data) |
title_full_unstemmed |
Synphne accelerated stroke rehabilitation system : data analytics and cloud computing (Business Data) |
title_sort |
synphne accelerated stroke rehabilitation system : data analytics and cloud computing (business data) |
publishDate |
2017 |
url |
http://hdl.handle.net/10356/72213 |
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1759854412673581056 |