The purpose of this project is to engage students in applying mathematical concepts to real-world scenarios, fostering a deeper understanding of linear regression, piecewise functions, and exponential models. By collecting and analyzing data related to their interests, students will gain practical skills in predicting trends and making informed decisions. This experience aims to connect mathematical theory with tangible outcomes, encouraging students to reflect on the broader implications of their findings and the limitations of mathematical models in diverse contexts.

Students will develop the ability to construct and interpret linear and exponential functions, including piecewise functions, to analyze real-world data. They will enhance their self-directed learning skills by using feedback and self-reflection to refine their understanding and application of mathematical models. Additionally, students will gain insights into the limitations of these models when applied to environmental and economic scenarios, fostering a deeper comprehension of how mathematics can be used to predict and understand complex phenomena.

Students will produce a climate change impact report using data from a local environmental organization, featuring linear regression models and piecewise functions to predict temperature trends and seasonal variations. They will also develop an economic forecast presentation using data from a local business or financial institution, employing exponential functions and linear regression to analyze market growth and historical trends. Additionally, students will design an interactive digital map illustrating local traffic patterns, utilizing linear regression and piecewise functions to inform city planning decisions, complemented by a presentation on the real-world applications of their models.

Begin the project with a dynamic 'Data Dive Day,' where students actively gather data from their local environment, such as temperature fluctuations or traffic patterns. This hands-on activity will serve as the foundation for their linear regression analysis, sparking curiosity and setting the stage for deeper exploration. Encourage students to collaborate and share their initial findings, fostering a sense of community and shared purpose as they embark on their mathematical modeling journey.

Students will participate in a 'Math in the Real World' exhibition, where they present their projects to peers, teachers, community partners, and local stakeholders. Each student will display visual representations of their data and models, including interactive graphs, digital maps, and infographics. During the exhibition, students will engage in discussions with visitors, explaining their learning journey, the real-world applications of their mathematical models, and the insights gained from their data analysis. This event will serve as a platform for students to showcase their understanding of mathematical concepts and their ability to apply them to real-world scenarios.