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Using JMP® to Predict the Adoption of Animals at Austin Animal Center g Hind Manou & Imran Selim MBA Students, Analytics Concentration, Oklahoma State.

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Presentation on theme: "Using JMP® to Predict the Adoption of Animals at Austin Animal Center g Hind Manou & Imran Selim MBA Students, Analytics Concentration, Oklahoma State."— Presentation transcript:

1 Using JMP® to Predict the Adoption of Animals at Austin Animal Center g Hind Manou & Imran Selim MBA Students, Analytics Concentration, Oklahoma State University Every year, approximately 7.6 million companion animals end up in US shelters. Many animals are given up as unwanted by their owners, while others are picked up after getting lost or taken out of cruelty situations. We have gathered data from Austin Animal Center and analyzed the data to interpret how animal shelters can modify their strategy and effort to increase animal adoption rate. We did a follow up analysis to determine the factors that contribute to the return of an animal to its owner. ABSTRACT METHODS RESULTS CONCLUSION

2 Data Selection & Preparation
- 26,729 observations - 8 input variables and 4 variables created - 1 target variable - Variables selection using Forward Variable Selection Day, Time TransformedAge Sex_1, Sex_2 AnimalType BreedOutcome ABSTRACT METHODS RESULTS CONCLUSION

3 Data Analysis Neural Network Logistic Regression Decision tree
The sex and Neural Network -Misclassification rate is 23.58% -People prefer to adopting neutered animal -In the neutered group: the younger tends to be adopted more, especially if it is a cat. Logistic Regression Decision tree - Validation Misclassification rate is 23.41% -Whether the animal is neutered or spayed is the most decisive variable -Likelihood of adoption decreases as the age increases -The odds of being adopted for a cat is 1.23 times more than that of a dog -Misclassification rate is 23.22% -If the animal is neutered and it is young it is most likely to be adopted -People tend to adopt more after 6:00 pm ABSTRACT METHODS RESULTS CONCLUSION

4 Decision Tree is the best model
Model Comparison Decision Tree is the best model The most important variables are: type of surgery, age, time of adoption and Animal Type. ABSTRACT METHODS RESULTS CONCLUSION

5 Additional Analysis: Return to Owner
- The odds of being adopted is 4.32 times more for dog than that of cat. - Older animals are more likely to be returned to the owner - After 12:00 pm the chances of return to owner increases. ABSTRACT METHODS RESULTS CONCLUSION

6 Recommendations - Consider increasing number of employees in the afternoon and the evening to assist people that want to adopt or reclaim an animal. - Increase the chance of adoption for both male and female animals by performing neutering and spaying surgeries. - Cats have a higher chance to be adopted and dogs have a higher chance to be returned to the owners. - Include the age factor in the marketing plan: Younger animals are more likely to be adopted Older animals are more likely to be returned to owners ABSTRACT METHODS RESULTS CONCLUSION

7 Name Email Phone LinkedIn
Team Members Name Phone LinkedIn Hind Manou (405) hind-manou / Imran Selim (405) mran-selim / Hind Manou Imran Selim


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