I completed a comprehensive data analysis project in R, focusing on understanding the psychological regions of the United States and their correlations with political, economic, social, and health factors. The project was based on the paper titled "Divided We Stand: Three Psychological Regions of the United States and Their Political, Economic, Social, and Health Correlates" from apa.org.
- US_state_data.xlsx: This Excel file served as the primary dataset containing information about different states in the United States, including political, economic, social, and health-related variables.
- US_state_data.csv: A CSV file derived from the Excel dataset for easier data manipulation in R.
- Google Trends Data: To enhance the analysis, I collected data from Google Trends (https://trends.google.com/trends/) and used it to fill empty columns in the US_state_data dataset.
- Data Preprocessing: I imported the US_state_data.csv into R, filled in the missing columns using Google Trends data, and cleaned and prepared the dataset for analysis.
- Data Scaling: To ensure compatibility and comparability, I scaled the two sets of data (existing and Google Trends data) between 0 and 1, ensuring they were on the same scale.
- Descriptive Statistics: I computed and reported various descriptive statistics to summarize the dataset, providing insights into the central tendencies, variability, and distribution of the data.
- Data Visualization: I created various plots, similar to those in BasicPlots.R, to visually represent the relationships between the psychological regions and other factors. These plots help in understanding the correlations and trends in the data.
- Documentation: I created a commented script in R , making it easy for others to understand and replicate the analysis. Additionally, I generated an R Markdown PDF (please find
.rmdfile) that provides a detailed report of the entire analysis process, including data preprocessing, scaling, statistical findings, and visualization.
This project showcases my data analysis and visualization skills, as well as my ability to collect, clean, and merge data from multiple sources and my command in R programming and the presentation of findings through descriptive statistics and visualizations.