Caso de estudio - Doctorado Ciclo III

This project presents a comprehensive time series analysis of monthly measles cases reported in Jere Local Government Area, Borno State, Nigeria, from 2016 to 2022. The analysis involves data preprocessing, visualization, stationarity testing using the Augmented Dickey–Fuller (ADF) test, and model identification through ACF and PACF plots. An ARIMA model was fitted to the transformed (square-rooted) series to forecast measles incidence for future periods. The results include decomposition of the series into trend, seasonal, and random components, along with forecast plots and confidence intervals (80% and 95%). The study offers valuable insights into the temporal patterns of measles transmission, supporting evidence-based public health planning for disease control and prevention in the region.

This project involves analyzing the IMDb Top 1000 movies dataset using SQL to uncover trends, insights, and patterns in film data. The dataset includes information such as movie titles, release years, genres, ratings, directors, and runtime. Key objectives of the project include: Extracting and filtering top-rated movies by genre, decade, or director. Identifying trends in movie ratings over time. Analyzing the most frequent genres and prolific directors in the top 1000. Comparing average ratings across different genres and time periods. Using aggregate functions, joins, and subqueries to derive meaningful insights. This project demonstrates strong data querying, filtering, and analytical skills using SQL, with an emphasis on data-driven storytelling and clean, efficient query design.

Resolução de duas questões sobre MCMC