<p>I must submit this tomorrow. This is a revision. The prompt is :</p>
<p>“Your statement should include your purpose in pursuing graduate study, any research you wish to pursue, and your future career goals. Write your statement on a separate sheet and submit it directly to your department.”</p>
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<p>I am pursuing graduate studies in applied statistics because the ability to analyze data and forecast associated trends has wide application. With a MS in applied statistics, I will be well prepared to extract meaningful descriptive data, analyze that data backwards and forwards for trends, and provide stakeholders with the necessary information to complete their task. As a result of the University of Iowa having a solid statistics program to complement their actuarial science program, I will be able to obtain a thorough understanding of the statistics behind the tools of an actuary while simultaneously learning statistical essentials such as probability theory, inference, and modeling. Upon graduation, I will work in a data driven occupation within the private sector or for an agency of the federal government.</p>
<p>I hope to apply optimization to insurance and finance. Having studied engineering, I have seen how statistics can optimize processes and improve efficiency. Prior to the Load and Resistance Factor Design (LRFD) method, engineers used the Allowable Strength Design (ASD) method exclusively to calculate the weight structural members (beams, columns, base plates, etc.) had to withstand. The ASD method multiplies all load effectse.g. snow, wind, carsby the same amplification factor to account for uncertainty in estimating how much weight a structural member must support. The LRFD method takes into account the certainty with which we can estimate certain loads; the weight of a piece of machinery can be estimated with more certainty than the load effects from a group of workers occupying a space for a Christmas party. Probabilistic models were used to come up with larger amplification factors for load magnitudes with high uncertainty and smaller amplification factors for load magnitudes with low uncertainty. Where the ASD method says you would need a column that can support 1500 pounds, the LRFD method would more accurately require a column that can support 1000 pounds. Less required strength means a smaller I-beam could be used which results in money saved in steel. </p>
<p>I am also interested in learning more about data mining. This field of statistics would make good use of my computer programming skills. With my programming experience in C++, Visual Basic Applications in Excel, MATLAB, and Python, I will be able to use my degree in statistics to glean the last modicum of pertinent information from a set of data.</p>
<p>Actuarial sciences use in fields other than insurance is appealing to me. The application of statistical modeling to finance in the form of asset and liability valuation is very important; fallacies in the assumptions and logic used in these applications can have serious monetary consequences. Unlike Bayesian statistics, frequentist statistics gives little attention to prior knowledge of the process being modeled. Disregard of prior knowledge of the process being modeled is especially deleterious in the world of finance. For example, securities are connected to world events; world events do repeat themselves and the likelihood to repeat can be studied. If a negative world event is on the horizon, this should be factored into the statistical model I am looking forward to studying Bayesian statistics and seeing how it can be applied in finance and insurance to improve the accuracy of the estimating process.</p>
<p>The statistics program at the University of Iowa has everything I need to achieve a thorough understanding of the fundamentals of statistics. Considering the quality of your statistics programas indicated by your national rankingand the strength of your actuarial science programas demonstrated by your CAE designation by the SOAI feel confident in your programs ability to prepare me for the actuarial exams and a career in the actuarial sciences or statistics.</p>