This study explores the relationship between CBN primary auction stop rates and secondary market yields for 364-day Nigerian Treasury Bills (NTBs) during January–May 2026. Using 101 daily secondary market yield observations collected from my trading desk at Sterling Bank and 12 bi-weekly CBN auction stop rates, I apply five analytical techniques — Exploratory Data Analysis, Data Visualisation, Hypothesis Testing, Correlation Analysis, and Linear Regression — to investigate yield dynamics, pricing efficiency, and the predictive power of primary auction outcomes on secondary market behaviour. The analysis reveals a statistically significant and narrowing primary-secondary yield spread, strong inter-market correlation, and a regression model that explains approximately 87% of secondary yield variance. Developed as a Case Study 1 (Exploratory & Inferential Analytics) submission for Data Analytics II at Lagos Business School (MMBA programme), Prof Bongo Adi, April 2026. Built in Quarto with dual R and Python implementations.

Este reporte presenta un análisis exploratorio de datos centrado en la clasificación de los pozos según la formación geológica alcanzada a su profundidad final (TD). A través del procesamiento del dataset, se evalúa la distribución y frecuencia de las unidades litoestratigráficas terminales, permitiendo identificar los objetivos geológicos y horizontes de perforación más recurrentes

Gas Consumption & Billing Analytics — Mall Facilities Dharmattan Nigeria Limited | May 2025 – May 2026 by Ifeoluwa Olosunde

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This study explores the relationship between CBN primary auction stop rates and secondary market yields for 364-day Nigerian Treasury Bills (NTBs) during January–May 2026. Using 101 daily secondary market yield observations collected from my trading desk at Sterling Bank and 12 bi-weekly CBN auction stop rates, I apply five analytical techniques — Exploratory Data Analysis, Data Visualisation, Hypothesis Testing, Correlation Analysis, and Linear Regression — to investigate yield dynamics, pricing efficiency, and the predictive power of primary auction outcomes on secondary market behaviour. The analysis reveals a statistically significant and narrowing primary-secondary yield spread, strong inter-market correlation, and a regression model that explains approximately 87% of secondary yield variance. Developed as a Case Study 1 (Exploratory & Inferential Analytics) submission for Data Analytics II at Lagos Business School (MMBA programme), Prof Bongo Adi, April 2026. Built in Quarto with dual R and Python implementations.