This presentation explains the core ideas of hypothesis testing in statistics

Coral Interaction Matrix

ustralia is home to some of the world's most unique and diverse wildlife, yet many species are facing increasing threats from habitat loss, invasive species, climate change, and human activity. This data story explores the current state of Australia's biodiversity and evaluates whether conservation efforts have been successful in protecting threatened species. Using data from the Department of Climate Change, Energy, the Environment and Water (DCCEEW), the Australian Bureau of Statistics (ABS), and the Threatened Species Index (TSX), the project examines both the scale of the biodiversity crisis and the effectiveness of conservation responses. The analysis begins by highlighting the large number of plant and animal species currently classified as threatened. It then investigates Australia's conservation efforts through the expansion of protected areas and increased monitoring of threatened species over time. While these initiatives demonstrate a growing commitment to conservation, the findings reveal that many threatened wildlife populations continue to decline overall. However, the story also identifies examples of successful species recovery, showing that targeted and sustained conservation programs can produce positive outcomes. By combining multiple data sources and interactive visualisations, this project provides a balanced view of Australia's conservation journey. The results suggest that although significant progress has been made in habitat protection and wildlife monitoring, further investment and long-term action will be required to reverse biodiversity loss and secure the future of Australia's unique wildlife

The analysis uses official Madrid and Barcelona premise data, official municipal boundaries, INE ADRH 2023 income, INE Censo 2024 population, and MITMS/spanishoddata OD data for one complete Monday-Sunday week. This report tests one spatial hypothesis: OD-derived dynamic demand components and functional corridor exposure add explanatory power beyond static residential demand in grid-discretised active service-premise intensity models, with fixed-theta negative-binomial fits used as the main overdispersion-sensitive comparison. The hypothesis is tested descriptively, not causally. The observed point pattern is the location of active service premises. The line pattern is a set of high-flow OD desire-line corridors derived from hourly MITMS mobility flows. The main statistical comparison is between static population-income intensity, dynamic OD intensity, dynamic OD plus corridor exposure, and a full static plus dynamic plus corridor specification.

Published 5 charts visualisation for assignment 3, Data Visualisation and Communication (2610)

Five interactive data visualisations exploring Australia's chronic pain crisis — the country's third-largest disease burden affecting 3.6 million Australians, yet its missing national health priority. Charts examine disease burden, demographics, diagnosis delays, treatment access, and human impact. Data sourced from AIHW, Chronic Pain Australia, and Painaustralia (2020–2025).

Inflation is usually told through a single number. But a slowing inflation rate does not mean prices are falling; it means they are still rising, only a little less quickly than before. The pressure people actually feel comes from a narrower basket — housing, food, transport, energy and insurance — and from whether wages are keeping up. These five charts follow that pressure, using open data from the Australian Bureau of Statistics (ABS).

EXPECTED EDGE