The Western MFE program seeks intellectually curious students with strong quantitative and communication skills who are looking to combine technical and analytical skills with a “big picture” understanding of the relationship between the economy and financial markets. Please briefly explain how my educational background provides me with the foundation required for MFE coursework and limit the explanation into 100 words:
Education                                                                                  
College of Science, North China University of Technology, Beijing, China                                      09/2020-07/2024
Bachelor of Science in Statistics to be granted in July 2024        GPA: 3.97/4.0
Computer Literacy                                                                          
SPSS, R Language, SAS, Excel, Python, Amos Graphics, MySQL, PyCharm, C++, Anaconda, Jupyter Notebook, PPT, Word, Photoshop

Publications                                                                                
•  Xiaoxun Zhu, Jinfei Xue, Ming Hu, Zhantian Liu, Xiaoxia Gao, Weijia Huang, Low-carbon Economy Dispatching of Integrated Energy System with P2G-HGT Coupling Wind Power Absorption Based on Stepped Carbon Emission Trading, Journal of Renewable & Sustainable Energy, ISSN: 1941-7012, E-ISSN: 1941-7012, Publisher: AMER INST PHYSICS, Aug. 2023
•  Weijia Huang, Analysis of the TikTok Live Broadcast Experience and Its Influencing Factors, Statistics and Application, ISSN Print: 2325-2251, ISSN Online: 2325-226X, Publisher: Hans Publishers, Aug. 2023

Academic Experience                                                                             
Analysis & Strategic Research on the Current Situation of Housing Factors Affecting the Fertility Intentions of Different Income Groups - Based on CGSS2021 Data Analysis                                                                       03/2023-Now
Supervisor: Prof. Liwen Xu
Team Leader – Team of 4
•  Established project objectives for participation in the Innovation & Entrepreneurship Training Project. Initiated and led the team in conducting preliminary qualitative analysis, identifying housing factors as a significant influence on residents’ fertility intentions. 
•  Utilized CGSS2021 data to develop a multiple regression model, examining the effects of housing factors on fertility intentions across various income groups. Key factors analyzed include housing area, property ownership, and the number of properties owned.
•  Performed rigorous testing using ordered logit regression, subsample regression, and sample replacement methods to ensure robustness of the findings.
•  Generated research recommendations based on the analysis of 500 preliminary survey questionnaires, offering policy suggestions in the areas of macro-level regulation, supervision, financial leverage, and economic subsidies, to explore feasible measures to enhance residents’ fertility intentions.
•  Completed a research paper of *** words, scheduled for submission to the Journal of Capital Normal University by September.
 
Hype: Seeking the Best Products, Achieving Beautiful Skin - Investigation on the Influence of Hype Platforms on Facial Skincare Product Purchase Decisions in the Beijing Area                                                                                 12/2022-04/2023
Team Member -Team of 5
•  Collected 635 valid responses out of 785 distributed questionnaires, incorporated professional literature and secondary data for comprehensive analysis.
•  Employed descriptive statistics to showcase the demographic characteristics of the respondents, and combined findings from text mining and secondary data to evaluate the overall consumption patterns of XiaoHongShu (Little Red Book) users.
•  Conducted factor analysis using SPSS to determine the key factors impacting consumers’ purchasing decisions on the hype platform. Extracted and categorized consumer characteristics. Analyzed and quantified the effects of different key factors on consumers’ purchasing decisions using AISAS model and structural equation modeling.
•  Implemented the TOPSIS model to rank popular skincare brands. Conducted a case study on the top-ranked brand, Lancôme, providing enhancement recommendations to other brands regarding sales channels, hyping content, target audience, in addition to market regulation and consumer advice. 
•  Awarded 1st Prize (undergraduate group) at 13th National Undergraduate Market Research & Analysis Competition of Beijing 

Research on Market Demand & Consumer Preferences for Ready-to-Eat Meals in Beijing                                       12/2022                                                                                                           
Team Leader -Team of 5
•  Led data collection efforts by distributing 264 questionnaires and successfully obtained 232 valid responses. Incorporated professional literature and secondary data to support comprehensive analysis.
•  Conducted descriptive statistical analysis to examine the demographic attributes of the participants. Studied the fundamental opinions and purchasing behaviors of various groups towards ready-to-eat meals. Utilized factor analysis to extract four common factors related to purchasing decisions for categorizing frequent and infrequent buyers.
•  Applied a logistic regression model to identify six significant variables that influence the consumption behavior of frequent buyers. Developed targeted marketing strategies from production, research and development, and sales perspectives. Formulated marketing strategies for infrequent buyers based on characteristic analysis, emphasizing product, brand, and pricing considerations.
•  Summarized four key conclusions from the analysis results and provided three recommendations for the advancement of the ready-to-eat meal industry.

Analysis of the TikTok Live Broadcast Experience and Its Influencing Factors                                             08/2022-09/2022                                                                                                           
Supervisor: Associate Prof. Xuefeng Zhang
•  Applied the rough set theory and the simplified algorithm to analyze the data obtained from Python programming and performed 0-1 normalization for data processing.
•  Developed a visually interactive interface to facilitate the analysis and interpretation of the results.
•  Examined the usage patterns and preferences of college students towards TikTok through the analysis of data, investigated the loyalty of college students towards the TikTok app and the impact of TikTok live streaming on their behavior.
•   Completed an 8000-word research paper on the findings of the study and published it in Statistics and Application in Aug. 2023.

Low-carbon Economy Dispatching of Integrated Energy System with P2G-HGT Coupling Wind Power Absorption Based on Stepped Carbon Emission Trading                                                                  12/2022-08/2023                                                                                                         
Team Member -Team of 6
•   Contributed to the development of a low-carbon economic dispatch model for the Integrated Energy System (IES), incorporating power-to-gas (P2G) and hydrogen-doped gas units (HGT) under a stepped carbon trading mechanism.
•   Supervised the research process and conducted formal analysis of the proposed model. Demonstrated the effectiveness of the proposed model in improving wind power utilization, reducing wind abandonment costs, and decreasing CO2 emissions by analyzing different scenarios and linearizing the established model.
以下是我已经学习过的部分相关课程和分数：
Economics : 微观经济学91， 宏观经济学	98，国民经济核算95，经济法92，
Finance： 证券投资分析95，  证券市场93，  市场营销管理 93， 
Mathematics：线性代数I  92，数学分析II （1）81、数学分析II （2）91、概率论92、大数据机器学习97
Statistics：统计认识实习、数理统计95、统计课程设计、统计学导论95、抽样技术89、统计实务93、市场调查方法96、多元统计分析96、非参数统计95、时间列序分析90