Hi guys I'm applying for MS in biostatistics with an undergraduate major in biological sciences and a minor in math.
I'm not a native speaker >.<
PLZ point out any mistakes, any suggestions and what you think. Need your help!!
As plenty data are being generated in public health and biomedical research, biostatistics is applied in growing number of studies related with human health to draw valid conclusions. For me, a career in biostatistics perfectly suits my professional competence, my interest in using mathematical methods and my eagerness in advancing the public's health.
3 years ago I chose to major in biology in college, wishing to approach my long-lasting dream: devote myself to biomedical research. I joined Prof. XXX's lab of neurological diseases when I was a sophomore. There, I independently researched on mitochondria oxidation abnormality in Alzheimer's Disease (AD) based on bio-imaging, and also participated in making animal model of AD. The over 1-year research experience in Prof. XXX's lab improved my research skills a lot. In summer 2013, as an outstanding undergraduate in School of Life Sciences, I was offered full scholarship to attend the Summer Undergraduate Research Program at the University of YYY. In this ten-week program, I worked fulltime in Dr. MMM's Olfactory System Lab, investigating neural activation transmission in the olfactory system. Although this field was rather new for me, I was soon able to work independently and finally made progress in visualizing glutamate transmission with a new glutamate sensor. Besides my research ability, my English communication skills also greatly improved. Although my TOEFL score is just fair, I had no difficulty communicating with others, especially on academic topics.
These lab-based research experiences helped me not only to get a comprehensive understanding of biomedical research, but also to identify my interest in biostatistics. Throughout the time I studied and researched in biological sciences, I was interested in how scientific conclusions are drawn from original data. Suggested by Prof. XXX, I read Introductory Biostatistics by Dr. Chap T. Le and many other publications to equip myself with more knowledge in biostatistics. However, I was surprised to find statistical misusages in published research papers. For example, a misusage of t-test, the author wanted to know if group A and group B are significantly different from each other. Instead of using t-test on group A and group B, he misused t-test to compare the control group with group A and group B respectively. After searching on Google Scholar, I found many journals about this severe problem: huge number of statistical mistakes were included in research papers due to lack of knowledge in statistics. I gradually realized the importance of biostatistics in biomedical research and became more interested in it.
Drawn by my interest in mathematics, programming and modeling, I took a wide variety of courses in college. In summer 2012, I attended a course, Bayesian Modeling of Perception, taught by PPP from Baylor College of Medicine. I self-studied Matlab Programming to prepare for this course, yet found my mathematical knowledge too poor to fully understand the ideas of this interesting course. To improve my mathematical ability, I then started a dual degree in Mathematics and Applied Mathematics and took courses such as Probability, Statistics, Advanced Algebra, Abstract Algebra, Functions of Real Variables and Stochastic Processes. As I accumulated more knowledge in mathematics, I got more interested in applying it to biological research, so I also chose courses such as Computational Vision (tanght by QQQ from UCLA), Mathematical Modeling in the Life Sciences and Methods in Bioinformatics. In Mathematical Modeling in the Life Sciences, our group conducted a project on optimizing the Consensus Decision Making Model of fish, in which I read papers, discussed the potential methods with my teammates, and did most of the Matlab programming and simulating. In Methods in Bioinformatics, I learned how mathematics is used in bioinformatics, for example, how Hidden Markov Model is used in identifying a CpG island. I did a project on the H5N1 virus, in which I used NCBI Genbank to get the HA gene sequences of H5N1, built phylogenetic tree, analyzed the territorial features of the sequences, and then pointed out several possible routes of their transmission. Furthermore, I attended two courses on C programming, Introduction to Computation, and Algorithm and Data Structure and Computer Operation. All these theoretical and applied courses went hand in hand, improved my mathematical, programming and creative capacities.
Interesting as lab-based biomedical research is, I gradually found it deviates from my initial dream: improving health conditions of human. The biomedical research is much more ahead of the treatment today. In the meantime, as I got more familiar with biostatistics and public health, I found that rather than biomedical research, biostatistics is a more practical area where I can approach my dream. Its applications effectively provide solutions for problems of human health and disease, for example, how to design a sound clinical experiment and how to analyze the incomplete clinical data. It perfectly suits my dream to improve the public's health and my mathematical and programming skills. I finally decided that my career should be in biostatistics instead of biomedical sciences.
To prepare for my career, I began a more relevant project under the guide of Prof. XXX and the teacher of Statistics, Prof. ZZZ: identify autism-related genes that cause deficiency in neuron migration during brain development. With the data of the neurons' positions generated by fluorescent imaging, I used multivariate linear regression to create the quadratic curve equation of the estimating brain surface, built the spatial distribution model of the migrating neurons, and sought quantitative methods to identify the genes that lead to the deficiency. It was difficult to find an efficient identifying method with enough tolerance of experimental error, but with the help of Prof. ZZZ, I've successfully revised Kolmogorov-Smirnov test and identified some genes. I learned a lot about how to deal with huge amount of data.
Thanks to my diverse learning and research experiences, I've found my perfect field of interest - biostatistics, which combines my professional skills and eagerness for human health studies. To prepare for the graduate study, I registered in a SAS course and Ordinary Differential Equation this semester and will continue taking more, such as Survival Analysis and Categorical Data Analysis.
My ultimate goal is to improve the public's health with my professional abilities. To fulfill this goal, I want to be a biostatistics researcher. The Master of Science degree in ***** would be the perfect first step for me, as it offers a desirable comprehensive education, plentiful research opportunities and a broad range of cooperation with other departments (and companies). I am most interested in clinical trial and design. Based on my multi-discipline knowledge and research experiences in biological science and statistics, I have confidence that I am eligible for your program and will also contribute to it.
I'm not a native speaker >.<
PLZ point out any mistakes, any suggestions and what you think. Need your help!!
As plenty data are being generated in public health and biomedical research, biostatistics is applied in growing number of studies related with human health to draw valid conclusions. For me, a career in biostatistics perfectly suits my professional competence, my interest in using mathematical methods and my eagerness in advancing the public's health.
3 years ago I chose to major in biology in college, wishing to approach my long-lasting dream: devote myself to biomedical research. I joined Prof. XXX's lab of neurological diseases when I was a sophomore. There, I independently researched on mitochondria oxidation abnormality in Alzheimer's Disease (AD) based on bio-imaging, and also participated in making animal model of AD. The over 1-year research experience in Prof. XXX's lab improved my research skills a lot. In summer 2013, as an outstanding undergraduate in School of Life Sciences, I was offered full scholarship to attend the Summer Undergraduate Research Program at the University of YYY. In this ten-week program, I worked fulltime in Dr. MMM's Olfactory System Lab, investigating neural activation transmission in the olfactory system. Although this field was rather new for me, I was soon able to work independently and finally made progress in visualizing glutamate transmission with a new glutamate sensor. Besides my research ability, my English communication skills also greatly improved. Although my TOEFL score is just fair, I had no difficulty communicating with others, especially on academic topics.
These lab-based research experiences helped me not only to get a comprehensive understanding of biomedical research, but also to identify my interest in biostatistics. Throughout the time I studied and researched in biological sciences, I was interested in how scientific conclusions are drawn from original data. Suggested by Prof. XXX, I read Introductory Biostatistics by Dr. Chap T. Le and many other publications to equip myself with more knowledge in biostatistics. However, I was surprised to find statistical misusages in published research papers. For example, a misusage of t-test, the author wanted to know if group A and group B are significantly different from each other. Instead of using t-test on group A and group B, he misused t-test to compare the control group with group A and group B respectively. After searching on Google Scholar, I found many journals about this severe problem: huge number of statistical mistakes were included in research papers due to lack of knowledge in statistics. I gradually realized the importance of biostatistics in biomedical research and became more interested in it.
Drawn by my interest in mathematics, programming and modeling, I took a wide variety of courses in college. In summer 2012, I attended a course, Bayesian Modeling of Perception, taught by PPP from Baylor College of Medicine. I self-studied Matlab Programming to prepare for this course, yet found my mathematical knowledge too poor to fully understand the ideas of this interesting course. To improve my mathematical ability, I then started a dual degree in Mathematics and Applied Mathematics and took courses such as Probability, Statistics, Advanced Algebra, Abstract Algebra, Functions of Real Variables and Stochastic Processes. As I accumulated more knowledge in mathematics, I got more interested in applying it to biological research, so I also chose courses such as Computational Vision (tanght by QQQ from UCLA), Mathematical Modeling in the Life Sciences and Methods in Bioinformatics. In Mathematical Modeling in the Life Sciences, our group conducted a project on optimizing the Consensus Decision Making Model of fish, in which I read papers, discussed the potential methods with my teammates, and did most of the Matlab programming and simulating. In Methods in Bioinformatics, I learned how mathematics is used in bioinformatics, for example, how Hidden Markov Model is used in identifying a CpG island. I did a project on the H5N1 virus, in which I used NCBI Genbank to get the HA gene sequences of H5N1, built phylogenetic tree, analyzed the territorial features of the sequences, and then pointed out several possible routes of their transmission. Furthermore, I attended two courses on C programming, Introduction to Computation, and Algorithm and Data Structure and Computer Operation. All these theoretical and applied courses went hand in hand, improved my mathematical, programming and creative capacities.
Interesting as lab-based biomedical research is, I gradually found it deviates from my initial dream: improving health conditions of human. The biomedical research is much more ahead of the treatment today. In the meantime, as I got more familiar with biostatistics and public health, I found that rather than biomedical research, biostatistics is a more practical area where I can approach my dream. Its applications effectively provide solutions for problems of human health and disease, for example, how to design a sound clinical experiment and how to analyze the incomplete clinical data. It perfectly suits my dream to improve the public's health and my mathematical and programming skills. I finally decided that my career should be in biostatistics instead of biomedical sciences.
To prepare for my career, I began a more relevant project under the guide of Prof. XXX and the teacher of Statistics, Prof. ZZZ: identify autism-related genes that cause deficiency in neuron migration during brain development. With the data of the neurons' positions generated by fluorescent imaging, I used multivariate linear regression to create the quadratic curve equation of the estimating brain surface, built the spatial distribution model of the migrating neurons, and sought quantitative methods to identify the genes that lead to the deficiency. It was difficult to find an efficient identifying method with enough tolerance of experimental error, but with the help of Prof. ZZZ, I've successfully revised Kolmogorov-Smirnov test and identified some genes. I learned a lot about how to deal with huge amount of data.
Thanks to my diverse learning and research experiences, I've found my perfect field of interest - biostatistics, which combines my professional skills and eagerness for human health studies. To prepare for the graduate study, I registered in a SAS course and Ordinary Differential Equation this semester and will continue taking more, such as Survival Analysis and Categorical Data Analysis.
My ultimate goal is to improve the public's health with my professional abilities. To fulfill this goal, I want to be a biostatistics researcher. The Master of Science degree in ***** would be the perfect first step for me, as it offers a desirable comprehensive education, plentiful research opportunities and a broad range of cooperation with other departments (and companies). I am most interested in clinical trial and design. Based on my multi-discipline knowledge and research experiences in biological science and statistics, I have confidence that I am eligible for your program and will also contribute to it.
