Building Blocks of Success: 

Reflections on My Skills in Quantitative Analysis

Quantitative analysis has been an integral part of my academic and professional growth, starting with my involvement in agricultural research in high school. My skills in quantitative analysis are a result of my participation in agriscience fairs, my graduate coursework at the Bush School, and my work experience as a Graduate Assistant of Research (GAR) and the United States Department of Agriculture (USDA) National Agricultural Statistics Service (NASS). Through these experiences, I have developed a passion for research and analysis, learned the basics of statistics and econometrics, and expanded my skills in statistical programming and data visualization.

Developing a Passion: Agriscience Fair

My first introduction to scientific research and quantitative analysis developed a passion that has endured beyond my last competition. The National FFA Agriscience Fair competition encourages the use of scientific principles to answer relevant agriculture, food, and natural resource questions. My projects included research on genetically modified corn productivity, public perceptions and knowledge about agriculture, and consumer perceptions of agricultural product labeling. For each project, I conducted a scientific experiment, wrote a research article, and presented my findings to a panel of judges. To analyze my findings, I received assistance from an agricultural research scientist who utilized SPSS to determine the statistical significance of my results. With each project, I gained confidence in each step of the research process and found myself appreciating and enjoying research and analysis. This passion has driven my desire to expand my skills through coursework and work experiences. 

Learning the Basics: Graduate Coursework

I learned the basics of quantitative analysis, including descriptive and inferential statistics, multivariate regression analyses, non-linear analyses, and statistical programming, through coursework I completed in statistics and econometrics at the Bush School. Prior to attending the Bush School, I had very little experience with statistical software and did not fully understand the basics of statistics. I took two quantitative analysis courses in my first year of graduate school. The first course taught me various methods of research design, methods of data collection, calculation of descriptive and inferential statistics, and computation of data using statistical software (STATA). In the second course, I gained a deeper understanding of multivariate regression and non-linear regression analyses including probits, logits, quadratic, logarithmic, and difference-in-difference regressions. Understanding these statistical skills and the STATA statistical software has allowed me to apply quantitative analysis skills in a variety of settings, including additional coursework, graduate assistantships, and summer internships.

Expanding my Skills: Job Experience

Through graduate assistantships and summer internships, I honed my quantitative skills in areas such as statistical programming, data cleaning and validation, analytical software utilization, coding in R for data analysis and visualization, and leveraging my understanding of statistics to interpret inputs and outputs from analytical models. During the summer between my first and second year at the Bush School, I interned with USDA NASS as an agricultural statistics pathway trainee. This internship focused heavily on reviewing and analyzing data collected through surveys of agricultural producers across Texas and Oklahoma. I learned and utilized over 10 different proprietary software applications to clean, validate, and analyze the survey data to develop estimates for regional and national publications. I often was not creating models or calculating specific statistics; however, my understanding of statistics allowed me to understand the inputs and outputs from the analytical software in order to create more accurate estimates. After completing my internship, I began as a GAR under Dr. Lewis in the department. My position has focused on gathering and analyzing oil and gas data related to production, methane, and land ownership. For these projects, I have used the R coding language to gather, clean, analyze, and visualize the data. This has required me to independently learn coding skills in R using online forums, AI tools, and video courses. 

Conclusions & Takeaways

Though my competency in quantitative analysis is not expert level, the experience I gained from my participation in agriscience fairs, my graduate level coursework at the Bush School, and my job experience as an intern and GAR has created the building blocks for continued growth and development with this skill. My agriscience fair experiences in high school developed my passion for research and analysis which paved the way for me to learn and understand statistical skills in my coursework at the Bush School. This baseline allowed me to thrive in my internship and graduate assistantship by applying and expanding my skills in quantitative analysis. Today, I am able to analyze data using statistical programming softwares such as STATA and R, calculate descriptive and inferential statistics such as measures of central tendency and statistical significance, and apply various data visualization techniques to effectively communicate findings and insights. As I reflect on these experiences, I am excited to continue the growth and development through future endeavors.