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Titanic Data Analysis by R Data Language for Insights and Correlation

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Emerging Trends in Expert Applications and Security

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 841))

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Abstract

One of the very fatal and tragic events in the history, the Titanic tragedy had an impact on people for about 100 years. During the duration of the Titanic incident, it is believed that the ship charged ahead at speeds higher than what was recommended. The objective of this research paper is to apply different analysis methods of R to dataset to discover the attributes that the surviving passengers possessed. Ggplot2 is also utilized. From the results, the insights are discovered.

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References

  1. https://www.kaggle.com/mrisdal/exploring-survival-on-the-titanic

  2. Jun S (2016) Patent big data analysis by R data language for technology management. Int J Softw Eng Appl 10(1):69–78

    Google Scholar 

  3. R development core team (2015) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, http://www.R-project.org

  4. https://www.datacamp.com/community/blog/machine-learning-tutorial-for-r

  5. https://github.com/IQSS/workshops/blob/master/R/Rgraphics/Rgraphics.org

  6. Chatterjee T (2017) Prediction of survivors in titanic dataset: a comparative study using machine learning algorithms. Int J Emerg Res Manag Technol. Department of Management Studies, NIT Trichy, Tiruchirappalli, Tamilnadu, India

    Google Scholar 

  7. Singh A, Saraswat S, Faujdar N (2017) Analyzing Titanic disaster using machine learning algorithms. In: International conference on computing, communication and automation (ICCCA), pp 406–411

    Google Scholar 

  8. Biel Steven (1996) Down with the old canoe: a cultural history of the Titanic disaster. W.W. Norton, New York

    Google Scholar 

  9. https://www.analyticsvidhya.com/blog/2016/02/complete-tutorial-learn-data-science-scratch/

  10. Halpern, S (2011) Report into the loss of the SS Titanic: a centennial reappraisal. Stroud, Gloucestershire U.K., History

    Google Scholar 

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Correspondence to Shweta Bhardwaj .

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Khanna, S., Bhardwaj, S., Khurana, A. (2019). Titanic Data Analysis by R Data Language for Insights and Correlation. In: Rathore, V., Worring, M., Mishra, D., Joshi, A., Maheshwari, S. (eds) Emerging Trends in Expert Applications and Security. Advances in Intelligent Systems and Computing, vol 841. Springer, Singapore. https://doi.org/10.1007/978-981-13-2285-3_9

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