SOP revision Review--Must submit tomorrow. MS Statistics

[CHOCTICK]

Hello. I will be submitting this tomorrow. This is the 3rd draft so I hope it meets with everyone's approval. I am going for MS Statistics.

 

MBS 7107

 

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.

 

 

 

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.

 

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 effects—e.g. snow, wind, cars—by 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.

 

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.

 

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.

 

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 program—as indicated by your national ranking—and the strength of your actuarial science program—as demonstrated by your CAE designation by the SOA—I feel confident in your program’s ability to prepare me for the actuarial exams and a career in the actuarial sciences or statistics.

 

Edited January 7, 2013 by CHOCTICK

[selecttext]

You may want to rephrase your opening paragraph using a standardized format such as

 

"I am interested in such and such aspect of statistics". "This is an interesting and meaningful subdiscipline because". "I would like to research this further in order to". "The graduate degree will help me achieve my career goals of ... because"

 

Your second paragraph could easily be incorporated into your first. This would leave room to talk about your excellent preparation for a graduate degree and how wonderful of a student you are.

 

Is there a professor in the department whose research interests intersect with your own? Now would be the time to mention him or her. You can mention if you have made contact with a potential supervisor.

 

What you have written is not terrible but it isn't specific.

[fuzzylogician]

I have some specific comments below, but the main thing I would encourage you to work on is bringing yourself into this SOP. You describe a lot of generalities, including things that adcom surely already knows about its field, but there is not enough of you in there. Why are you interested in this field? What exactly are interested in? What do you want to do with these interests? Why this University in particular? There is some answer to all these questions but there should be more.

 

I am pursuing graduate studies in applied statistics because the ability to analyze data and forecast associated trends has wide applications. 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. Because the University of Iowa has a strong statistics program to complement its 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 plan to work in a data driven occupation within the private sector or for an agency of the federal government.

 

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 that structural members (beams, columns, base plates, etc.) had to withstand. The ASD method multiplies all load effects—e.g. snow, wind, cars—by 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.

There is nothing in this paragraph about YOU. It completely distracts from what should be the theme of this essay as given by the prompt you quoted. You're teaching adcom members things they must already know. You're not explaining why you are interested in this stuff. This paragraph needs to be edited or (probably) removed.

 

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.

More of this, please. Expand on your interest in data mining.

"glean the last modicum of pertinent information from a set of data": use less fluffy language.

 

Actuarial sciences’ use in fields other than insurance is appealing to me, too. 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.

Again, you are explaining theory to your teachers. Why does this interest YOU? What do you hope to learn and how do you hope to apply it in your future career?

 

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 program—as indicated by your national ranking—and the strength of your actuarial science program—as demonstrated by your CAE designation by the SOA—I feel confident in your program’s ability to prepare me for the actuarial exams and a career in the actuarial sciences or statistics.

You don't need to tell the University it's great, they are flattered enough that you chose to apply there. Cut the talk about their national rankings out; talk about the things that are relevant to you - the strengths that are relevant for the career you want to have, any particular courses they offer, other resources, faculty, collaborations with other departments, etc.

[CHOCTICK]

How about I replace the second paragraph with this. My engineering background plays a big part in why I want to study statistics.

 

 

After studying structural engineering for two years, I had an epiphany. Anyone can apply the engineering concepts I had been learning for the past two years. I do not want to apply the concepts; I want to formulate the concepts. Prior to the Load and Resistance Factor Design (LRFD) method, engineers used the Allowable Strength Design (ASD) method exclusively to calculate structure capacities. The ASD method multiplies all load effects—e.g. snow, wind, cars—by 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. I want to apply statistical methods to other areas to improve efficiency and realize cost savings.

[selecttext]

I think that you should hold your degree in higher esteem because not everyone can successfully accomplish an engineering degree. 

 

I have glanced at your paragraph. It is too technical and does not refer to your ideas and objectives. Perhaps you will find this format useful:

 

"While studying structural engineering, I became fascinated with LRFD because it represents a significant improvement over ASD. I believe that the statistical approach used in LRFD could be used in other facets of structural engineering, such as..., to improve the efficiency of ... Therefore, for my dissertation, I would like to... in order to".

 

Use this as a starting point and incorporate it into your first paragraph.

Edited January 7, 2013 by david.timerman

[fuzzylogician]

Again, only the first and last sentences tell me about you and your interests. Are the sentences in the middle going to teach the adcom something relevant they don't already know?

 

After studying structural engineering for two years, I came to the conclusion that I am not interested in simply applying the engineering concepts I had been learning, as engineers normally do. Instead, I want to have the knowledge that would allow me to formulate such concepts. For example .... (your example here, possibly stripped down to bare essentials if the adcom already knows this). By obtaining a degree in statistics, I hope to be able to apply statistical methods to other areas [of ______] and to improve efficiency and realize cost savings [in area].

[biotechie]

You definitely need to talk more about yourself in this essay. Why are YOU interested? What makes you special? How are the things that make you special and that you are interested going to make an impact? What do you want to do in your life, and how is this program going to help you?