We study the effect of promotions on attendance. We build a linear model to for predicting attendance using month, day of the week and an indicator variable for the bobblehead promotion

To understand the product design process we study here the Proctor and Gamble Laundry Soaps

This analysis is based on the pollution data that has been collected from the CityPulse project and the URL" http://iot.ee.surrey.ac.uk:8080/datasets.html”. This dataset consists of five air-pollution elements or attributes and they are Ozone (O3), Carbon Monoxide (CO), particulate matter (PM), Sulphur Dioxide (SO2) and Nitrogen Dioxide (NO2). In addition to timestamp, longitude, and latitude.

In the first part we calculated how much the price of the train ticket should be lowered to increase the public transportation by 10 percent. In this document we calculate tax that should be imposed to have a comparable effect on the train ticket prices

Traditional conjoint analysis.

DS-680- Marketing Analytics and operation Research. Commuters in Sydney can choose car or train as means of transportation. We use linear combination of four explanatory variables(car time,car cost,Train time,Train cost) to predict consumer choice.In this study we set a goal to increase the public transportation usage by 10 percent. How much should the train ticket prices should be lowered keeping all other explanatory variables constant? We can use the fitted logistic model to answer this question.

In this document handwritten digits are predicted using various models

In this document PCA is applied to reduce the dimensions of data set and then logistic and SVM are applied to compare their performance.