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    Modeling Scenario
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    1-001-MM-DeathAndImmigration-ModelingScenario
    We conduct a simulation of death and immigration, using a small set of "individuals", m&m candies or any two sided object (coin, chips), in which upon tossing a set of individuals we cause some to die and others then to immigrate. Modeling ensues!
    Modeling Scenario
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    1-141-MMGameRevisited-ModelingScenario
    It is assumed that the probability of an M&M chocolate, when tossed, falling on the M side is 0.5 The goal is to find a probability distribution of the probability q which is Pr(randomly chosen M&M falling M up when tossed).
    Modeling Scenario
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    1-001s-StochasticMDeathImmigration-ModelingScenario
    We develop a mathematical model of a death and immigration process using m&ms as a stochastic process with the help of probability generating functions (pgf). We start with 50 m&ms in a bag.
    Modeling Scenario
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    1-001a-MMDeathImmigration-Variation-ModelingScenario
    We model exponential death with m&m's as well as death with immigration.
    Article or Presentation
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    2009-Brian_Winkel-Population_modelling_with_MandMs
    Several activities in which population dynamics can be modeled by tossing M&M’s® candy are presented.
    Modeling Scenario
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    1-001B-DeathImmigrationMystery-ModelingScenario
    We describe a classroom activity in which students use M\&M candies to simulate death and immigration. Each student conducts an experiment with an immigration rate unique to that student - of that student's choice
    Potential Scenario
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    Potential Scenario
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    1980-Peastrel-Lynch-Armenti-Terminal velocity of a shuttlecock in vertical fall
    We have performed a straightforward vertical fall experiment for a case where the effects of air resistance are important and directly measurable.
    Modeling Scenario
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    5-077-MandMAttritionWarfare-ModelingScenario
    Students model attrition between two opposing forces using M&M candies and discover a system of linear differential equations of order one, often called the Lanchester equations.
    Article or Presentation
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    1980-Peastrel-Lynch-Armenti-Terminal_velocity_of_a_shuttlecock_in_vertical_fall
    This paper offers a set of data on a falling shuttlecock (the moving object in badminton) in air. How the authors collected the data is described fully and can be replicated easily by modern equipment.
    Modeling Scenario
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    4-035-ParEstSteadyState-ModelingScenario
    Students estimate parameters in a second order, linear, ordinary differential equations through analysis of the steady state solution. By applying a driver we can collect data in terms of the parameters and estimate these parameters
    Potential Scenario
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    1971-Carl_Metzler-Usefulness Of Two Compartment Open Model In Pharmacokinetics
    Compartment models are widely used in pharmaceutical research to quantitate the kinetics of absorption, distribution, metabolism and excretion of a drug. In this article two applications of the two compartment open model are discussed.
    Modeling Scenario
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    1-017-DiseaseSpread-ModelingScenario
    Using a grid and m&m candies, we simulate the spread of disease. Students conduct the simulation and collect data to estimate parameters (in several ways) in a differential equation model for the spread of the disease.
    Potential Scenario
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    2008-Brewer-EtAl-Fitting ordinary differential equations to short time course data
    In this paper, we present a survey of existing algorithms and describe the main approaches. We also introduce and evaluate a new efficient technique for estimating ODEs linear in parameters particularly suited to situations where noise levels are...
    Potential Scenario
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    2007-Choisy-Guégan-Rohani-Mathematical Modeling of Infectious Diseases Dynamics
    After presenting general notions of mathematical modeling (Section 22.2) and the nature of epidemiological data available to the modeler (Section 22.3), we detail the very basic SIR epidemiological model (Section 22.5).
    Potential Scenario
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    2014-Blomhøj-EtAl-Compartment models
    An overview of compartment models with many rich illustrations and much attention to various numerical methods in solutions of the resulting differential equations using Matlab. Also included is a section on the limitations of compartment models.
    Potential Scenario
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    2014-John_Cimbala-Dynamic System Response
    In this learning module, we discuss the dynamic system response of sensors and their associated electronic circuits.
    Potential Scenario
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    2008-Lawson-Marion-An Introduction to Mathematical Modelling
    This is a broad based set of notes with sections: Building Models, Studying Models, and Using Models. No depth on any model, no solution strategies, but good references to models, and general approaches that apply in most situations are offered.
    Potential Scenario
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    1987-MS_Greenwood-Using videotapes to study underdamped motion of a pendulum
    Using a video camera to study the effects of air resistance acting on pendulum bob, ping-pong ball, styrofoam spheres, and brass spheres.
    Modeling Scenario
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    3-065-UpDown-ModelingScenario
    We model the height of a launched object which is subject to resistance proportional to velocity during its flight. We ask questions about the motion as well, e.g., highest point or apex and terminal velocity.