oxford123
Oct 24, 2019
Graduate / Statistics (Data Science) - Personal Statement [2]
Please review my essay.
Feel not very competitive compared to other applicants, but don't konw how to improve. Any feedback is welcome!
Mathematics manifests as the world's sole universal language, turning complicated behaviors, patterns, and observations into symbols readable by any mathematician in any country. No other field's impacts spans so wide: cryptography, aero/astro, biotechnology-at the root of every sigfnicant 21st century industry, at the root of all science, is mathematics. As I dedicated my undergraduate studies to different aspects of mathematics, I began to consider which part of the field I should choose to further devote myself. In the end, the application of mathematics, speficially through data science, attracted me the most because the applications of data science feel as ubiquitious as math itself. Data science is not a standalone set of specified theories, pertinent to one specific industry. Rather, data science grows increasingly vital to a multitude of industries every day.
For some background on me, I am currently finishing my final year at the Hong Kong University of Science and Technology, majoring in the Statistics and Financial Mathematics track within the Department of Mathematics. After completing the general mathematics courses, I started to increasingly focus on courses which are more closely related to statistics. Those courses changed my perspective not only of statistics, but also of mathematics as a whole. Before those courses, I thought of statistics merely as the summarization of data. The more I learned, the more I realized how wrong my initial perception was. In short, statistics displays all latent information from a basic data set. It is not a summarization, but rather an excavation tool, something that can produce something out of seemingly nothing. My first classes were simple. Statistical Inference explained to me distributions and estimators. Regression Analysis taught me how to analyze data sets and estimate the relationships between variables. Stochastic Modeling and Survival Analysis showed me how statisticians transform general behaviors into mathematical models. The rewarding experiences of these introductory courses encouraged me to find out more about the capacity of statistics. Along the way, I was continuously reminded how important my ability to program would be.
Before my entry into University, I had no experience in programming. My first programming course focused on the Java language. Initially, it was a difficult time for me. I struggled to apply the concepts taught in lectures to the class laboratory sessions. However, my experience began to change during a solo class project that required us to create a Mastermind game. This was the first time that the theoretical lessons I had learned fully applied to a real-life practice. Soon after, I would take another programming course, focusing on C++, where there were weekly projects that needed to be finished in pairs. My partner was majoring in Computer Science. As we programmed together, I often found that we differed from each other in our approaches to programming. He often proposed a more effective way. He simply knew more about the field. From him, I learned that programming never has a standard answer, and that I should explore many applications of programming instead of focusing on the course lectures only. Thus, alongside my exploration of mathematics, I began exploring the many applications of programming.
In the summer of 2018, I worked as a teaching assistant in a Data Science Training Camp designed for students from my high school. After one week of instruction, the campers attempted group projects about data analysis, such as forecasting influenza rates based on Google search results and meteorological data. While teaching is a powerful tool for learning, the camp also gave me an opportunity to learn more from my fellow instructors. As I taught and learned simultaneously, I began to realize how powerful data science could be. It was also my first time using numerous programming languages, such as R and MATLAB. These languages worked in different ways than the fundamental programming languages I had learned previously. Computation and analytics could not only be completed in less lines of code, but the code was also significantly more productive than traditional code. Coding had never felt so efficient and productive. After that summer, I knew the study data science was the field within mathematics that I wanted to devote myself to.
Apart from these experiences, I've also worked on a banking and finance research team. The reports from our team pointed out that the macroeconomics market is periodical and that the market's future performance could be predicted through modelling. We enumerated and analyzed a long list of variables that linked to market behaviors, and our research was well received by the rest of the company. After the internship, when I was taking courses about financial mathematics at university, I found I can understand those concepts more easily. Along with teaching, I've found that application is the greatest enhancer for learning.
With my background knowledge of statistics and related areas such as data science and finance, I am eager to explore more in graduate school. Because the curriculum of my bachelor's degree focused more on general statistics and financial mathematics, I am excited to take more courses about specific data analytics tools and to have more opportunities to work on projects that are related to data analytics. I recognize how important the experience of solving real problems is for this applied major.
Additionally, certain courses provided in this program, such as Big Data and Machine Learning, can give me more chances to learn necessary skills that I currently lack. This program provides advanced courses that give me the tools to become the best data scientist I can be.
I aim to have an occupation related to data analytics after obtaining my master's degree. Currently, I am researching as much as I can in my final year of my bachelor's, exploring areas where data analytics has seen huge growth, such as finance and insurance. If I can acquire more knowledge and information about data analytics from both school courses and personal research, I feel confident about my future occupation plan.
As far as I am concerned, this program of your institute is exactly the path towards my goal. Therefore, I sincerely hope that I will have the opportunity to be admitted and to realize my dream.
Please review my essay.
Feel not very competitive compared to other applicants, but don't konw how to improve. Any feedback is welcome!
the path towards my goal
Mathematics manifests as the world's sole universal language, turning complicated behaviors, patterns, and observations into symbols readable by any mathematician in any country. No other field's impacts spans so wide: cryptography, aero/astro, biotechnology-at the root of every sigfnicant 21st century industry, at the root of all science, is mathematics. As I dedicated my undergraduate studies to different aspects of mathematics, I began to consider which part of the field I should choose to further devote myself. In the end, the application of mathematics, speficially through data science, attracted me the most because the applications of data science feel as ubiquitious as math itself. Data science is not a standalone set of specified theories, pertinent to one specific industry. Rather, data science grows increasingly vital to a multitude of industries every day.
For some background on me, I am currently finishing my final year at the Hong Kong University of Science and Technology, majoring in the Statistics and Financial Mathematics track within the Department of Mathematics. After completing the general mathematics courses, I started to increasingly focus on courses which are more closely related to statistics. Those courses changed my perspective not only of statistics, but also of mathematics as a whole. Before those courses, I thought of statistics merely as the summarization of data. The more I learned, the more I realized how wrong my initial perception was. In short, statistics displays all latent information from a basic data set. It is not a summarization, but rather an excavation tool, something that can produce something out of seemingly nothing. My first classes were simple. Statistical Inference explained to me distributions and estimators. Regression Analysis taught me how to analyze data sets and estimate the relationships between variables. Stochastic Modeling and Survival Analysis showed me how statisticians transform general behaviors into mathematical models. The rewarding experiences of these introductory courses encouraged me to find out more about the capacity of statistics. Along the way, I was continuously reminded how important my ability to program would be.
Before my entry into University, I had no experience in programming. My first programming course focused on the Java language. Initially, it was a difficult time for me. I struggled to apply the concepts taught in lectures to the class laboratory sessions. However, my experience began to change during a solo class project that required us to create a Mastermind game. This was the first time that the theoretical lessons I had learned fully applied to a real-life practice. Soon after, I would take another programming course, focusing on C++, where there were weekly projects that needed to be finished in pairs. My partner was majoring in Computer Science. As we programmed together, I often found that we differed from each other in our approaches to programming. He often proposed a more effective way. He simply knew more about the field. From him, I learned that programming never has a standard answer, and that I should explore many applications of programming instead of focusing on the course lectures only. Thus, alongside my exploration of mathematics, I began exploring the many applications of programming.
In the summer of 2018, I worked as a teaching assistant in a Data Science Training Camp designed for students from my high school. After one week of instruction, the campers attempted group projects about data analysis, such as forecasting influenza rates based on Google search results and meteorological data. While teaching is a powerful tool for learning, the camp also gave me an opportunity to learn more from my fellow instructors. As I taught and learned simultaneously, I began to realize how powerful data science could be. It was also my first time using numerous programming languages, such as R and MATLAB. These languages worked in different ways than the fundamental programming languages I had learned previously. Computation and analytics could not only be completed in less lines of code, but the code was also significantly more productive than traditional code. Coding had never felt so efficient and productive. After that summer, I knew the study data science was the field within mathematics that I wanted to devote myself to.
Apart from these experiences, I've also worked on a banking and finance research team. The reports from our team pointed out that the macroeconomics market is periodical and that the market's future performance could be predicted through modelling. We enumerated and analyzed a long list of variables that linked to market behaviors, and our research was well received by the rest of the company. After the internship, when I was taking courses about financial mathematics at university, I found I can understand those concepts more easily. Along with teaching, I've found that application is the greatest enhancer for learning.
With my background knowledge of statistics and related areas such as data science and finance, I am eager to explore more in graduate school. Because the curriculum of my bachelor's degree focused more on general statistics and financial mathematics, I am excited to take more courses about specific data analytics tools and to have more opportunities to work on projects that are related to data analytics. I recognize how important the experience of solving real problems is for this applied major.
Additionally, certain courses provided in this program, such as Big Data and Machine Learning, can give me more chances to learn necessary skills that I currently lack. This program provides advanced courses that give me the tools to become the best data scientist I can be.
I aim to have an occupation related to data analytics after obtaining my master's degree. Currently, I am researching as much as I can in my final year of my bachelor's, exploring areas where data analytics has seen huge growth, such as finance and insurance. If I can acquire more knowledge and information about data analytics from both school courses and personal research, I feel confident about my future occupation plan.
As far as I am concerned, this program of your institute is exactly the path towards my goal. Therefore, I sincerely hope that I will have the opportunity to be admitted and to realize my dream.
