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Early Childhood Obesity Data Analysis Essay

1023 Words5 Pages

Introduction What is obesity? Obesity is a condition that is associated with having an excess of body fat, defined by genetic and environmental factors that are difficult to control when dieting. Obesity is classified as having a Body Mass Index (BMI) of 30 or greater. BMI is a tool used to measure obesity. Now let us see what is childhood obesity? Doctors and scientists are concerned about the rise of obesity in children and teens because obesity may lead to the following health problems: i) Heart disease ii) Type 2 diabetes iii) Asthma, iv) Sleep apnea v) Social discrimination. Why Childhood obesity is bad . In the U.S.A, early childhood obesity continues to be a public health issue. The United States Centers for Disease Control (CDC) …show more content…

Many times people understand the ideas of analytics but get frustrated in communicating with others because they are missing the framework of analytics that helps organize and communicate the broad range of analytic processes and uses to business audiences. The framework of analytical ideas is to take four kinds of processes and organize them into categories. The categories are Descriptive Analytics, Diagnostic Analytics, Predictive Analytics, and Prescriptive Analytics. Below is a summary of the stages of data analysis: • Descriptive analytics: What happened? • Diagnostic analytics: Why did it happen? • Predictive analytics: What could happen in the future? • Prescriptive analytics: How should we respond to those potential future events? Or what should we do? Statement of the Problem Childhood obesity is one of the major problems in the U.S.A. Previous researchers have found many reasons and are working to identify how to stop obesity. There are many collected data used for that purpose. Those data are sometimes structured, but most of the time they are unstructured data using collected data from different sources, analyzing it and optimizing it for the better prediction. Optimizing the collected data prescriptive analytics can reduce childhood obesity by identifying

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