About
I specialize in Statistical analysis, Data visualization, Data Analytics and Economic analysis. With a strong foundation in Economics and Quantitative Methods, I leverage various analytical tools to enhance decision-making and business strategy.
Skills
Proficient in SQL, Python, IBM SPSS, R, Tableau, and Power BI. Adept at predictive modeling, regression analysis, multilevel analysis, and clustering techniques.
SQL
Python
IBM SPSS
R
Power BI
STATA
Web Scraping
Microsoft Excel
Projects
These are some of my most interesting projects including data cleaning and transformation.
BBC Goodfood recipes Dashboard
This project analyzed BBC Goodfood recipes, scraping data for different food types like Quick & Easy, Vegan, and Vegetarian. The data was cleaned with tidyverse, and attributes like preparation time, rating, servings, and nutrition were examined. Linear and random forest regression models were created using tidymodels to predict preparation time based on various inputs. Key R libraries used: Rvest, Shiny, Shinycssloaders, Tidyverse, Tidymodels, ggdist, bs4Dash, and tidyquant.
Economic Growth and International trade
This project investigates the impact of international trade on economic growth in seventeen Sub-Saharan African countries, including Nigeria, South Africa, and Ghana, among others (2010 - 2021). Recognizing the diverse economic landscapes and challenges these countries face, the study employs quantitative research methodology, utilizing secondary data from reputable sources such as national statistics offices and World Bank databases.
