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I have written about 30 academic assignments, with statistics. And one day, I received an assignment: Applied Statistics project. It was about forecasting stock price, and you had to create a predictive model based on market trends. I had never done it before. The material was tough: We had to analyze different models and select the best one for a specific set of data. The best way to get a feeling for the project is to have an idea of the problems, but also to understand the structure of the project. So here it goes:
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Applied Statistics projects are complex, high-tech, and highly specialized. However, they do require us to employ our quantitative and computational skills, in order to provide a solid theoretical foundation for other applications of statistics in engineering, business, and science. There are different types of applied statistics projects in different areas. For instance, it might be a research project to investigate the effectiveness of an industrial process on reducing manufacturing defects, or a project to forecast the success of an agricultural product in a specific market. These are just a few examples of how applied statistics projects are
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I have spent the past few years in pursuit of my Masters’s degree and am currently working towards completing it at a top-ranked university. Although it has been a rigorous and challenging task for me, I’ve also learned a lot about applied statistics, which is my area of interest. In my opinion, applying statistical methods is just as crucial for the success of my future career as is mastering the technical side of mathematics. My experience with applied statistics began in my undergraduate studies, where I had taken classes in regression analysis and correlation.