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    Modeling Scenario
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    1-109-EmployeeAttrition-ModelingScenario
    This scenario models the loss of employees and the employer's attempt to retain them through stock options. It most naturally is solved with a first-order linear decay model with two populations.
    populationlinear growthdecayemployeeattrition
    Modeling Scenario
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    1-035-DotseroVolcanoEruption-ModelingScenario
    In this scenario, we use Carbon-14 dating of the Dotsero volcano in Colorado as a way of emphasizing this multistage process of modeling.
    exponential decayhalf-lifedecayEuler's methodcarbon datingdecay rateCarbon-14Dotsero volcanovolcano
    Modeling Scenario
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    1-080-DrugAdministration-ModelingScenario
    A simple drug administration situation is modeled with only two observations.
    decaybloodstreamdrugrate constantadminister
    Modeling Scenario
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    1-160-HeartDeathRate-ModelingScenario
    Students simulate experience from a given data set which represents the heart death rate during the period 2000 - 2010 using several approaches to include exponential decay, difference equation, differential equation, and parameter estimation...
    dataheart death rate
    Modeling Scenario
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    1-116-TropicalStormWindspeeds-ModelingScenario
    We model the decay of tropical cyclone winds once a storm makes landfall. We use data from two recent storms from the National Hurricane Center to estimate parameters emanating from a differential equation using a first order exponential decay model.
    hurricanedecaytropical stormcyclones
    Modeling Scenario
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    1-002-Tossing-ModelingScenario
    We offer students simulation experience or data from a simulation and ask them to model the simulation using several approaches, to include exponential decay fit, difference equation, and differential equation.
    Modeling and simulationexponentialdecaydice
    Modeling Scenario
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    1-024-MalariaControl-ModelingScenario
    This project offers students a chance to make policy recommendations based on the analysis of models using both linear (exponential decay) and non-linear (logistic growth) differential equations.
    population dynamicsmalariaPolicyDecision-makingEuler's methodpharmacokineticsmosquitoimproved Euler's methodHuen's methodUS Army
    Modeling Scenario
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    1-124-WorldPopulation-ModelingScenario
    We build models of world population using data to estimate growth rate.
    population dynamicshumangrowth ratevarying growth rate
    Modeling Scenario
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    1-026-Evaporation-ModelingScenario
    We provide data on evaporation of 91% isopropyl alcohol in six different Petri dishes and one conical funnel and on evaporation of water in one Petri dish. We ask students to develop a mathematical model for the rate of change in the respective...
    evaporationconealcoholPetri dish
    Modeling Scenario
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    1-001d-HotelPopulationDecay-ModelingScenario
    You will be modeling the following situation: 100 people are in a hotel. Each day, each person has a random chance of 50% of leaving the hotel. No new people enter the hotel. Before you run the simulation in MATLAB, answer some questions.
    simulationlogisticexponential decayfitting
    Modeling Scenario
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    1-085-DrugBolus-ModelingScenario
    Given data on the concentration of a drug in the plasma of a human in mg/L at certain time intervals in hours can we determine the rate at which the drug leaves the plasma as well as the initial amount administered in a intravenous bolus of the drug?
    concentrationsum of square errorsbolusdrugrate constantadminister
    Modeling Scenario
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    1-150-CancerTherapy-ModelingScenario
    This activity builds upon elementary models on population growth. In particular, we compare two different treatment models of cancer therapy where in one, surgery happens before therapy and in the other, surgery happens after therapy.
    population dynamicsphage therapyexponential growthcancerwater treatmentdecaysurgery
    Modeling Scenario
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    1-170-CensusModeling-ModelingScenario
    Students who have studied models for population are likely to be familiar with the exponential and the logistic population models. The goal here is to explore the role of modeling assumptions in choosing which model to use.
    logistic growthexponentialpopulationU.S. Census DataassumptionGoogle SheetsUnites StatesGuatemala
    Modeling Scenario
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    10-100-InsectOutbreaks-ModelingScenario
    We use a system of difference equations that incorporates a temperature-dependent MPB population growth rate to model the outbreak and recovery cycle in mountain pine beetle-infested forests.
    ecologyclimate changeinsectinsect outbreaksinsect outbreaksolitary wave
    Modeling Scenario
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    1-107-ClothDry-ModelingScenario
    We build a mathematical model for the rate of drying in a wet cloth while hanging in air. A model can be based on underlying physical principles (analytic) or based on observations and reasoned equations, but no physical assumptions (empirical).
    dryingclothevaporation
    Modeling Scenario
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    1-052-SaltWaterTanks-ModelingScenario
    We offer three mixing problems, of increasing order of difficulty, in which salt is coming into a tank of water and upon instantaneous mixing is leaving the tank.
    salttankmixing
    Modeling Scenario
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    6-025-WhalesAndKrill-ModelingScenario
    Students will use Excel to observe qualitative behavior in a simulation of a predator-prey model, with blue whales and krill as the predator and prey populations, respectively.
    krillwhalepredatpr-prey
    Modeling Scenario
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    1-058-WaterClocks-ModelingScenario
    We apply Torricelli's Law to the task of building a water clock in which the height of the water in a container falls at a constant rate when the container has a hole in the bottom to let the water flow out.
    flowTorricelli's Lawspigotswater clock
    Modeling Scenario
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    1-090-EmptySphericalTank-ModelingScenario
    We model the emptying of water from a spherical tank. First, we pump out water at a constant rate. Second, we allow the water to exit through a small hole in the bottom of the tank. We seek to determine how fast the water level is falling in both...
    VolumesphereTorricelli's Lawtimingspherical tankfluidempty
    Modeling Scenario
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    1-122-SpreadPEV-ModelingScenario
    We present data on world sales data of plug-in electric vehicles (PEVs) and request a model on the rate of change in sales over time, leading to prediction as to number of PEVs in the future.
    datalogisticpredictionspreadplug-in vehiclePEV