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    Potential Scenario
    212

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    2012-Augustus-Wali-Mathematical Modeling of Uganda Population Growth
    The purpose of this paper focuses on the application of logistic equation to model the population growth of Uganda using data from 1980 to 2010 (inclusive).
    population growthlogistic growthDrug and Alcohol detoxificationcarrying capacityvital coefficients
    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
    Potential Scenario
    313

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    53

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    1999-Lomen-Lovelock-Data Sets from text Differential Equations Graphics-Models-Data
    Data selected by field is presented, e.g., chemistry, electricity, growth, motion, population, miscellaneous.
    dataEstimate
    Modeling Scenario
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    282

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    1-127-FishHarvesting-ModelingScenario
    We offer students a harvesting model for operating a fishery over a 25 year horizon and ask them to write a report on optimal harvesting policy with their analyses for fishing industry experts (not necessarily mathematicians).
    Management Of Dataoptimal controlfisherieslogisticharvestingmaximum sustainable yield
    Potential Scenario
    191

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    43

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    2000-Dwayne-Anderson-Estimates of the future membership of the Church of Jesus Christ of Latter-Day Saints
    Thus, the purpose of this paper is to model the membership of the Church of the Latter Day Saints from the available data on membership from 1844 to 2000.
    population dynamicslogisticLatter-Day Saints
    Modeling Scenario
    362

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    202

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    6-021-AcornsRodentsSnakes-ModelingScenario
    Students are given the opportunity to build a three tropic level model in which snakes eat rodents, rodents eat acorns, and acorns grow and occasionally mast.
    predationforestsnakesrodentsacornstrophic levelmasting
    Modeling Scenario
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    1-019-RocksInTheHead-Modeling Scenario
    We describe an experiment with data on the perception of the individual mass of a collection of rocks in comparison to a 100 g brass mass. Students use the logistic differential equation as a reasonable model and estimate parameters.
    logistic growthparameter estimationexperiment
    Potential Scenario
    190

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    45

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    2013-Alicia_Caldwell-Students Rise to the Challenge of Modeling Yeast Growth Despite Sour Hiccups from Imperfect Data
    This paper describes a lab in which students in an Applied Mathematics in Biology course observe the growth of Saccharomyces cerevisiae, a yeast strain, in differing sugar concentrations for use in learning modeling.
    Saccharomyces cerevisiaelogisticyeastdeathgrowthsugaralcohol
    Potential Scenario
    137

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    37

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    2014-Danielsen-Sørensen-Using authentic sources in teaching logistic growth
    This 12 page offering develops issues and questions about using historical materials to motivate mathematics study and develops 9 very rich exercises
    real datalogistichistorical materials
    Modeling Scenario
    644

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    545

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    1-032-WordPropagation-ModelingScenario
    This activity is a gentle introduction to modeling via differential equations. The students will learn about exponential growth by modeling the rate at which the word jumbo has propagated through English language texts over time.
    Googleexponential growthlanguageword problemsetymologyNgrampropagationJumbo
    Modeling Scenario
    326

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    151

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    1-001c-PopulationDecayThenSome-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.
    simulationoccupancypopulationhotel
    Modeling Scenario
    263

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    122

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    1-084-GoingViral-ModelingScenario
    Students employ randomization in order to create a simulation of the spread of a viral disease in a population (the classroom). Students then use qualitative analysis of the expected behavior of the virus to devise a logistic differential equation.
    simulationlogisticrandomfittingpartial fractions
    Modeling Scenario
    318

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    413

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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
    m&mMystery Novelsimmigrationexperimentdeath
    Modeling Scenario
    677

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    229

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    5-026-Evictions-ModelingScenario
    In this project, students develop two SIS models to study eviction trends in a population of non-homeowner households using an actual eviction rate. Students can calculate solutions, sketch the phase portrait, and determine long-term trends .
    carrying capacitycompartmentevictionhomeownerSIS modelhomelessness
    Modeling Scenario
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    184

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    1-125-DiceyPopulation-ModelingScenario
    We offer students an opportunity to generate data for their team on a death and immigration model using 12 and 20 sided dice and then pass on the data to another student team for analysis with a model they built. The key is to recover the...
    simulationimmigrationdeathdice
    Modeling Scenario
    315

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    150

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    1-111-SpreadOfInformation-ModelingScenario
    Students perform experiments to model spread of information within a population. Students collect data, determine essential components and parameters and build a mathematical model culminating with a separable linear first order differential...
    datalogisticracismprejudicemisinformationmemesspreaddisinformationinformationliesGoogle Trendscoinspennies
    Modeling Scenario
    240

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    49

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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).
    Probabilitystochastic processesBayesian methodsprobability distribution
    Modeling Scenario
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    189

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    1-053-SlimeSpread-ModelingScenario
    We offer a video showing real time spread of a cylinder of slime and challenge students to build a mathematical model for this phenomenon.
    spreadsheetsslime
    Potential Scenario
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    2019-Dimopulos-Heaney-Bukaida-IceCoverageInTheArcticClimateOverTime
    Through extensive research, it was found that the region’s oldest and thickest ice on this extent has significantly and continually decreased over the years.
    Antarctic foodd websBiodiversity declineice coveragepolar bear
    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!
    simulationimmigrationdeathSpanishdatsWinkelBrian Winkel