Level: Intermediate
Abhishek Gorla, Graduate Student, University of Connecticut School of Business
Happiness is increasingly becoming an acceptable measure of success for governments and companies alike, across the world. So, we have sourced the data compiled by the local government of Somerville conducted across three years as the sample to develop insights about happiness of people. Using JMP, we effectively cleaned the survey data and, through pre-visualization, identified the parameters that are most likely to play a role in a person’s happiness.
First, through linear regression, we identified parameters with high statistical significance that determine happiness of a person. Then we developed various models to classify the respondents into two groupings of “Happy” people and “Not Happy” people.
Then, we sub-divided these “Not Happy” people into various focus groups using a hierarchal clustering method and observed that each group had different parameters that will likely make them happier. Using this information, governments will be able to target their programs and resources better while the people in the cities will feel more valued.
We have not only stumbled across some very interesting details about what makes happy people happy, but were able to design an efficient service delivery model for the government to convert unhappy people into happy people.