November 11, 2016

This lesson plan by an experienced high school physics teacher was created specifically to accompany the PhET simulation "Alpha Decay". It is intended for students who have had prior exposure to half-life and a fundamental understanding of nuclear decay. It provides guided directions to help students make predictions and verify their ideas through data tables and charts. As it progresses, students investigate a specific radioactive decay scenario, using the simulation to compare results of multiple trials. The lesson, as a whole, is designed to encourage deeper thinking about what half-life means in terms of single particles and larger samples. The alpha decay simulation, which must be open and displayed to complete this activity, is available from PhET at: Alpha Decay. This lesson, which meets multiple national standards for science and math, targets AP and algebra-based physics. See Related Materials for a simpler activity on alpha decay appropriate for Grades 8-10. This lesson is part of PhET (Physics Education Technology Project), a large collection of free interactive simulations for science education.

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Interpret functions that arise in applications in terms of the context

For a function that models a relationship between two quantities, interpret key features of graphs and tables in terms of the quantities, and sketch graphs showing key features given a verbal description of the relationship.?

Relate the domain of a function to its graph and, where applicable, to the quantitative relationship it describes.?

Calculate and interpret the average rate of change of a function (presented symbolically or as a table) over a specified interval. Estimate the rate of change from a graph.?

Interpret expressions for functions in terms of the situation they model

Interpret the parameters in a linear or exponential function in terms of a context.

Summarize, represent, and interpret data on two categorical and quantitative variables

Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.

Fit a function to the data; use functions fitted to data to solve problems in the context of the data.

Understand and evaluate random processes underlying statistical experiments

Decide if a specified model is consistent with results from a given data-generating process, e.g., using simulation.