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Sumin Han

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Sumin Han EDUCATION 2011- Present

Ph.D.

Business Administration

University of Tennessee, Knoxville

(Concentration in Statistics I Minor in Marketing)

Thesis Topic: Joint mode/ for the high-dimensional heterogeneous data with complex structure.

Advisor: Russell Zaretzki 2011

Statistics (Graduate Program)

University of California, Riverside

2007

Mathematics

Riverside Community College

Marketing Business Administration

Sookmyung Women's University, Korea

2006 2003

M.B.A. B.A.

Sookmyung Women's University, Korea

(Minor in Telecommunication)

EMPLOYMENT 2014

Instructor, Business Administration, University of Tennessee, Knoxville

2011

Research Assistant, University of Tennessee, Knoxville, USA

2006 - 2007

Research Assistant, Korea Labor Institute (KLI), South Korea

2005 -2006

Research Assistant, Korea Economics Research Institute (KERI), South Korea

2005 -2007

Program Coordinator, Le Cordon Bien Hospitality MBA, South Korea

2005 Summer

Internship (Marketing Pmt), Industrial Bank of Korea (IBK), South Korea

CERTIFICATIONS November 2011

Google Adwords Certification

CONFERENCE PROCEEDINGS AND PRESENTATIONS Sumin Han, Neeraj Bharadwaj, Kang Bok Lee, Russell Zaretzki (2014). "The Paths to Market

Penetration," A1nerica11 Marketing Association Sununer Conference Proceedings, American Marketing Association. Eunju Rho, Kang Bok Lee, and Sumin Han (2014), "Towards An Integrated Model of Contracting Determinants and Consequences: An Empirical Analysis." American Society for Public Administration's 751•Anniversary conference, Washington.

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TEACHING EXPERIENCE Instr uctor Full-time Teaching - STAT 201 Introduction to Statistics. Undergraduate. (Spring 2014; Fall 2014) Part-time Teaching Service Marketing (Fall; 2004)

Teaching Assistant -BZAN533 Quantitative Methods for Business Analytics (Fall 2015) -STAT578 Categorical Data Analysis (Fall 2015; Fall 2013; Fall 2012) -BZAN540 Applied Regression Analytics (Spring 2015) -BZAN543 Data Management for Business Analytics (Spring 2015) -BZAN548 Time Series Forecasting (Spring 2015) -STAT474 Data Mining and Business Analytics (Sprint 2013) -STAT572 Regression Analytics (Spring 2013) -STAT573 Design of Experiments (Fall 2013) -STAT579 Applied Multivariate Methods (Fall 2013) -STAT20 Introduction to Statistics (Spring 2013; Fall 2013)

FELLOWSHIPS/ GRANTS/ AWARDS 2011 -Present

Research and Teaching Assistantship, University of Tennessee, Knoxville

2004 - 2006

Research Assistant and Teaching Assistant, Department of Business Administration, Sookmyung Women's University, South Korea

2005

2nd place in presentation of Industrial Bank of Korea (IBK) Internship program; Strategy for target marketing by generation

2003 -2004

Department Administration Assistant, Sookmyung Women's University, South Korea

PROFESSIONAL CONSULTING 2007

"Study of Corporate Personality Measuring"

(PI=Suh, Yong-Gu, Sookmyung Women’s University, Supervisor =Hyundai Motor Company, http://worldwide.hyundai.com ). 2006-2007

"National Statistical Quality Diagnosis"

(Supervisor =National Statistic Office, Korea Labor Institute(KLI), http://www.kli.re.kr ). 2006

"A Study on the Development of Labor Management Roles for Stable Employment in the Age of Korea-US FTA"

(PI=Lim, Sang-Hoon, Hanyang University, Supervisor=Labor Management Joint Reemployment Assistance Center, South Korea)

TECHNICAL SKILLS R (Fluent); SAS (Fluent); STATA (Fluent); JMP (Fluent); MINITAB (Fluent); SPSS (Fluent); Sawtooth(Fluent); Google Analytics(Fluent); LISREL(Fluent); AMOS (Fluent); SQL (Good)

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STATISTICS TECHNIQUE FLUENCY  Joint Model: Longitudinal data and Multilevel data Data (Model Fitting; SAS Software)  Correspondence Analysis (Develop the model)  Non-Homogeneous Markov Chain: Longitudinal Data (Develop the model using Ordinal Logistic Distribution; STATA Software)  Non-Homogeneous Markov Chain: Simulation based on Panel Data ( R-software; OPTIM function)  Cox Proportional-Hazards Model: Longitudinal Data (Model Fitting; STATA Software)  Cox Proportional-Hazards Frailty Model: Medical Data (Model Fitting; SAS Software)  Fixed Effect Model: Labor Economics Panel Data (Model Fitting; STATA Software )  Random Effect Model : Longitudinal Data (Model Fitting; SAS Software)  GEE Model: Entomology Data (Model Fitting; SAS Software-'GENMOD' procedure)  Probit Model: Longitudinal Data (Model Fitting; STATA Software)  Polytomous Logistic Regression Model: Longitudinal Data (Model Fitting; STATA Software)  Dichotomous Logistic Regression Model: Longitudinal Data (Model Fitting; STATA Software)  Structural Equation Model: Cross-sectional Data (Model Fitting; SPSS, AMOS, LISREL Software)

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