CHENG QIAN

Bachelor of Science | Data Science
@ Portland State University

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Snail Length Prediction

This project explores relationships between snail shell lengths and various morphometric predictors using statistical learning methods. We performed exploratory analysis, evaluated transformations of the response variable, and built both simple and multiple linear regression models. Advanced techniques, including interaction exploration and random forests, were applied to improve prediction accuracy. The project combines rigorous data analysis with clear visualizations to understand key factors influencing snail growth patterns.

Birdsong Disturbance Analysis

This project investigates how recreational activities in urban parks affect birdsong behavior of local songbirds, focusing on humans and dogs as disturbances. Using field observations, we conducted exploratory analysis, Chi-squared test, logistic regression, and mixed-effects modeling to quantify effects on singing and chirping. Special attention was given to species-specific responses, particularly Song Sparrows. Visualizations and hazard ratios highlight behavioral trends, providing actionable recommendations for park management.

Targeted Campus Financial Aid Modeling

This project develops a data-driven framework to improve the accuracy and fairness of financial aid allocation in universities. Using campus card transaction records, we analyzed student consumption behaviors, identified anomalous spending patterns, and built evaluation models to screen students with the greatest financial need. Clustering methods were then applied to assign support levels and estimate reasonable aid amounts, highlighting how statistical modeling can inform more equitable and precise aid systems.

About me

Hello! I'm Cheng, currently pursuing a Bachelor's degree in Data Science at Portland State University, with an expected graduation in December 2025. I'm passionate about tackling real-world challenges by analyzing data, uncovering patterns, and discovering insights to turn evidence into actionable decisions.

Roles

Aspiring Data Scientist focused on extracting insights from data to solve real-world problems.

Skills

Proficient in Python, SQL, and R; experienced in machine learning, data visualization, and statistical modeling.

Values

Committed to leveraging data-driven decisions to turn complexity into clarity and deliver actionable results.

Interests

Enjoy experimenting with new recipes, hiking scenic trails, and experiencing diverse cultures.

Experience

Developed predictive models in Python; created interactive Tableau dashboards to visualize real-world datasets.

Personality

Analytical and detail-oriented, with a collaborative mindset and a passion for continuous learning.

Get in touch

Looking for opportunities in data analytics or applied data science, particularly roles involving statistical modeling, exploratory data analysis, and visualization. Dedicated to delivering actionable insights that support informed decision-making.