Statistical Analysis of Animal Adoption using R
Ridhi Anand1, Sherin Miriam Cherian2, Sriya Ravi3, Vaishnavi Agarwal4, Aswin Sampath5, S.Shreenidhi6, Akash Menon7, Srinath K R8, Umamaheswari .S9
1Ridhi Anand, School of Computing Science and Engineering, VIT, Chennai (Tamil Nadu), India.
2Sherin Miriam Cherian, School of Computing Science and Engineering, VIT, Chennai (Tamil Nadu), India.
3Sriya Ravi, School of Computing Science and Engineering, VIT, Chennai (Tamil Nadu), India.
4Vaishnavi Agarwal, School of Computing Science and Engineering, VIT, Chennai (Tamil Nadu), India.
5Aswin Sampath, School of Computing Science and Engineering, VIT, Chennai (Tamil Nadu), India.
6S.Shreenidhi, School of Computing Science and Engineering, VIT, Chennai (Tamil Nadu), India.
7Akash Menon, School of Computing Science and Engineering, VIT, Chennai (Tamil Nadu), India.
8Srinath K R, School of Computing Science and Engineering, VIT, Chennai (Tamil Nadu), India.
9Umamaheswari.S, School of Advanced Sciences, Mathematics Division, VIT, Chennai (Tamil Nadu), India.
Manuscript received on 01 May 2019 | Revised Manuscript received on 15 May 2019 | Manuscript published on 30 May 2019 | PP: 1213-1219 | Volume-8 Issue-7, May 2019 | Retrieval Number: G6357058719/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Animal shelters and rescue organizations hold the responsibility for catering to the needs of the animals that are abandoned or given up by their owners. The datasets are obtained from adoption centers in Austin, Texas between the years 2013 and 2017 and from Bloomington, Indiana between the years 2004 and 2017 with the aim of finding patterns and conducting data analysis on the different parameters that were involved with these adoption centers. Since 3 primary datasets dealing with different attributes related to the adoption centers are procured, all implementation in this study are purely based on this. Hence, the paper is designed to have several specific objectives and derived inferences for each of the datasets. The data is analysed with the statistical methods and visualization tools like bar plots, pie charts, line graphs, predictive regression models, all executed on R studio, an integrated development environment for R. The statistical model discussed in the data set enable us to make conclusions about why certain animals are euthanized, whether there is any particular preference for adoption, what kind of animals are taken in by adoptions centers, whether the total annual revenue gained by the adoption centers could be predicted and so forth. R has proven to be extremely useful because of its ease of use, excellent visualization tools and robust environment.
Keyword: Adoption, Dataset, Euthanasia, Parameters, Shelter.
Scope of the Article: Analysis of Algorithms and Computational Complexity.