JPPUBLICITY DIRECTOR

UC Davis economics junior preparing for my first professional steps

Third-year Economics student at UC Davis studying economic theory and quantitative methods while preparing to enter the job market.

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Work samples

Coursework and class projects that apply economic reasoning and quantitative analysis, showing how I approach problems and learn new tools.

  • STATISTICAL VARIANCE ANALYSIS GROUP PROJECT
    STATISTICAL VARIANCE ANALYSIS GROUP PROJECT

    Conducted one-way and two-factor ANOVA analysis in R on 150+ observations to evaluate how profession and region affect technology salaries, utilizing advanced mathematics and statistics ♦ Applied hypothesis testing, Box-Cox transformations, and outlier diagnostics to validate model assumptions and improve statistical fit, demonstrating strong analytical skills ♦ Calculated effect sizes and pairwise/non-pairwise confidence intervals to quantify and interpret each factor’s impact, developing a presentation to communicate the team’s recommendations

    R

About me

Third-year Economics student at UC Davis studying economic theory and quantitative methods while preparing to enter the job market.

I am Jesarine Penney, a third-year Economics student at UC Davis working toward a Bachelors degree. I have limited formal work experience and I am preparing to start my career, building skills and academic knowledge in economics and related areas.

Experience

PUBLICITY DIRECTOR

Davis Chinese Dance Team, Davis, CA · Dec 2024 - Present

K-BEAUTY BUSINESS OPERATIONS & MARKETING INTERN | ANALYTICS

Bemused, Seoul, South Korea · Jun 2026 - Aug 2026

STUDENT DATA ANALYST

Caltrans, Sacramento, CA · Sep 2025 - Jun 2026

Education

University of California, Davis: Agricultural and Environmental Sciences, 3.779 GPA

B.S in Managerial Economics, Minor in Statistics

Skills

MicroeconomicsMacroeconomicsEconomic data analysisBasic statisticsExcelCritical reading of economic research
Back to work

STATISTICAL VARIANCE ANALYSIS GROUP PROJECT

Conducted one-way and two-factor ANOVA analysis in R on 150+ observations to evaluate how profession and region affect technology salaries, utilizing advanced mathematics and statistics ♦ Applied hypothesis testing, Box-Cox transformations, and outlier diagnostics to validate model assumptions and improve statistical fit, demonstrating strong analytical skills ♦ Calculated effect sizes and pairwise/non-pairwise confidence intervals to quantify and interpret each factor’s impact, developing a presentation to communicate the team’s recommendations

R
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