This curricular unit is designed to complement the Revised 2026 AP Statistics Course Framework, particularly Units 1, 3, and 4, by providing students with an authentic, year-long ecological research experience. Rather than learning sampling methods and statistical inference as isolated mathematical procedures, students investigate meaningful questions about biodiversity, forest fragmentation, and carbon storage while applying the statistical practices used by professional ecologists. Throughout the unit, forest ecology serves as a common throughline that connects major topics across the AP Statistics curriculum.
Students begin by examining how ecologists design studies and collect representative data. After comparing simple random, stratified random, cluster random, and systematic sampling, students evaluate the strengths and limitations of each approach before selecting an appropriate sampling design for their own investigation. They then practice standardized field techniques and conduct ecological research at West Rock State Park, where they collect authentic data on tree diameter, bird communities, and insect herbivory.
As students progress through the course, they analyze the data they collected using the statistical methods introduced in AP Statistics. Depending on the research question being investigated, students construct confidence intervals and perform one- and two-sample t-tests, one- and two-proportion z-tests, or chi-square tests for homogeneity or independence. Throughout these investigations, students interpret their results within an ecological context while considering the practical consequences of Type I and Type II errors for conservation and environmental decision-making.
The unit culminates in students synthesizing multiple statistical analyses into an IMRaD (Introduction, Methods, Results, and Discussion) research paper. By integrating authentic field research with statistical reasoning, students experience AP Statistics as a tool for answering real scientific questions and communicating evidence-based conclusions about the natural world.
