Question 2: Technical and Quantitative Aptitude (REQUIRED)
The Ivey MSc in Business Analytics relies heavily on incoming students' comfort with, and understanding of, various quantitative analysis tools and technical skills. Please explain to the Admissions Committee how you have worked with, developed, or demonstrated an understanding of similar tools and skills, and how they will help you to succeed in the program. (500 words or less)
What should I modify to have a better essay? Thank you
In the course of Business And Technical Decision, I used SPSS to analyze the data of Chinese insurance industry, and therefore I have a deep understanding of insurance industry. According to the current convention of the insurance industry in China, for the property insurance company, 5 variables can be used to describe its business scope: premium income, reserves, number of claims, claims expenditure and outstanding claims. Among them, the premium income and claim payment are divided into 9 parts according to the characteristics of insurance. To find out the internal relations among the variables that constitute the essential characteristics of the property insurance companies, and find out the common characteristics or differences of the property insurance companies, I use the technical skills of bivariate correlation analysis, partial correlation analysis, multiple linear regression analysis and factor analysis. What's more, I also used strategic analysis model such as PESTEL and SWOT to compare the insurance industry in Mainland of China and Hong Kong. During the course of my research work, I came to realize decision making in the business world and economy is heavily affected by statistics and data analysis.
I know that business analytics refers to the skills, technologies, practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning. Business analytics focuses on developing new insights and understanding of business performance based on data and statistical methods. Therefore, business analytics uses statistical and quantitative analysis, data mining, predictive modeling, and multivariate testing to track key performance indicators, analyze trend data to assess the likelihood of future outcomes and use past performance to generate recommendations about how to handle similar situations in the future. For example, finance companies can use business analytics tools to process the vast amounts of data available at their disposal to unravel valuable insights on the performance of stocks and provide advice to the client whether to hold on or sell.
In the past three years, I have mastered related knowledge of some quantitative analysis tools and technical skills by learning the courses of Calculus, Possibilities & Amount Sat, Linear Algebra and Business Statistics. I hope that by learning in courses in Ivey, I could obtain the knowledge and skills to use technology and theoretical statistics, computer science and mathematics to effectively analyze and use big data in the field of natural science and social science.
The Ivey MSc in Business Analytics relies heavily on incoming students' comfort with, and understanding of, various quantitative analysis tools and technical skills. Please explain to the Admissions Committee how you have worked with, developed, or demonstrated an understanding of similar tools and skills, and how they will help you to succeed in the program. (500 words or less)
What should I modify to have a better essay? Thank you
In the course of Business And Technical Decision, I used SPSS to analyze the data of Chinese insurance industry, and therefore I have a deep understanding of insurance industry. According to the current convention of the insurance industry in China, for the property insurance company, 5 variables can be used to describe its business scope: premium income, reserves, number of claims, claims expenditure and outstanding claims. Among them, the premium income and claim payment are divided into 9 parts according to the characteristics of insurance. To find out the internal relations among the variables that constitute the essential characteristics of the property insurance companies, and find out the common characteristics or differences of the property insurance companies, I use the technical skills of bivariate correlation analysis, partial correlation analysis, multiple linear regression analysis and factor analysis. What's more, I also used strategic analysis model such as PESTEL and SWOT to compare the insurance industry in Mainland of China and Hong Kong. During the course of my research work, I came to realize decision making in the business world and economy is heavily affected by statistics and data analysis.
I know that business analytics refers to the skills, technologies, practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning. Business analytics focuses on developing new insights and understanding of business performance based on data and statistical methods. Therefore, business analytics uses statistical and quantitative analysis, data mining, predictive modeling, and multivariate testing to track key performance indicators, analyze trend data to assess the likelihood of future outcomes and use past performance to generate recommendations about how to handle similar situations in the future. For example, finance companies can use business analytics tools to process the vast amounts of data available at their disposal to unravel valuable insights on the performance of stocks and provide advice to the client whether to hold on or sell.
In the past three years, I have mastered related knowledge of some quantitative analysis tools and technical skills by learning the courses of Calculus, Possibilities & Amount Sat, Linear Algebra and Business Statistics. I hope that by learning in courses in Ivey, I could obtain the knowledge and skills to use technology and theoretical statistics, computer science and mathematics to effectively analyze and use big data in the field of natural science and social science.
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