PRINCIPLES OF DATA SCIENCE

In the united states, a larger position of the population is termed as being obese. Obesity creates a likelihood of the person developing other life-threatening health conditions that if not treated early or managed effectively can be fatal. Controlling obesity in the population is an important part of ensuring that the population is healthy and positively growing. This project is therefore aimed at understanding the relationship between age and weight among the population and in the process handle such concerns as the correlation between weight and development of lifestyle diseases such as diabetes, heart diseases and other diseases and conditions resulting from lifestyles led by the people. This research will be focused on establishing a correlation between age and obesity, a correlation between gender and the weight/ obesity cases and the relationship that exists between the age, gender, and likelihood of lifestyle-based health conditions such as diabetes.

kaggle. com/adu47249/obesity-stats/data ). The data consisted of the obesity statistic of the united states population. The zip file amounted to slightly over 1. 48MB with one file of original weight data. Microsoft Excel offers a good filtering and representational aspect of data in CSV fields and therefore proved a useful resource in data cleaning. Basic analysis and graphs can be done using the Microsoft Excel tool which makes it a useful part of the primary observation review of the data. One limitation of the data is that it does not have attached or associated information. There is only a brief mention of the last update of the data and the description of the data. Certain information such as the source/ person who uploaded the data are not mentioned.