Learning Goals
Students will be able to investigate bivariate data for growth, decay, cooling, finance, or population change to determine whether a linear, exponential, logarithmic, or logistic model is most appropriate.
Students will be able to build exponential functions from data to represent relationships between two quantities.
Students will be able to graph exponential and logarithmic functions using transformations and key features.
Students will be able to convert between exponential and logarithmic forms and evaluate logarithms, including common and natural logarithms.
Students will be able to apply logarithmic properties and change-of-base to expand, condense, and rewrite expressions.
Students will be able to solve exponential and logarithmic equations to answer questions about modeled situations.
Students will be able to evaluate the quality, limitations, and bias of an exponential, logarithmic, or logistic model using residuals, context, and available data.
Products
Annotated Investigation Notebook for a Real-World Exponential or Logarithmic Model
Each student maintains a research-style notebook documenting one focal data set, model decisions, calculations, graph revisions, and a personal analysis of fit and limitations. The notebook proves individual mastery of modeling, logarithms, and equation solving through evidence and reasoning.
Data Detective Expo Presentation and Model Defense
Teams present a formal investigation report and live model-defense presentation that synthesizes member notebooks into one justified conclusion with visuals, residual comparisons, limitations, and new questions. The presentation must show how the team handled conflicting evidence and why the chosen model best fits the context.
No rubric has been generated yet.