Ananya Dutta

The project here utilizes the concepts learnt in the probability models course - hypothesis testing, bootstrapping, maximum likelihood estimates, etc. and the same is then applied on real world data to draw influential results. The data used for this project is obtained from the Kaggle. The project here is to obtain distribution and other important statistical parameters for Rating of various Netflix shows and understand how the ratings are divided across years

• Collected data - Interarrival and Service times during rush hours at Subway, University of Cincinnati and used ARENA Input Analyzer to fit distributions to the data
• Developed a model for the working of Subway using ARENA and identified the existing problems
• Developed two improved models - first by increasing a reasource and second by cross-training the resources
• Proved statistically significant difference in the means of average customer queue time & length and average… Show more

• Collected data - Interarrival and Service times during rush hours at Subway, University of Cincinnati and used ARENA Input Analyzer to fit distributions to the data
• Developed a model for the working of Subway using ARENA and identified the existing problems
• Developed two improved models - first by increasing a reasource and second by cross-training the resources
• Proved statistically significant difference in the means of average customer queue time & length and average customer total time in the system for two models as compared to the base model by t-test, box-plots and confidence intervals using Output analyzer and Process Analyzer Show less

The objective of the project was to explore the TED Talks data and generate some interesting insights from it using data wrangling and visualization techniques in R.

This analysis is aimed at helping readers look at the popularity trend of ted talks over the years in terms of views,comments and ratings along with exploring its possible drivers like tags associated to the talk, occupation of the speaker, duration fo the ted talk, number of speakers etc. and finally identifying what makes… Show more

The objective of the project was to explore the TED Talks data and generate some interesting insights from it using data wrangling and visualization techniques in R.

This analysis is aimed at helping readers look at the popularity trend of ted talks over the years in terms of views,comments and ratings along with exploring its possible drivers like tags associated to the talk, occupation of the speaker, duration fo the ted talk, number of speakers etc. and finally identifying what makes the most viewed and the least viewed TED Talks. Show less