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1-018-LogisticPopModel-ModelingScenario

Author(s): Brian Winkel

SIMIODE - Systemic Initiative for Modeling Investigations and Opportunities with Differential Equations

Keywords: data analysis parameter estimation logistic Ciliate protozoa population limited growth paramecia Gause

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Abstract

Resource Image We offer artificial (toy) and historical data on limited growth population situations in the study of protozoa and lead students through several approaches to estimating parameters and determining the validity of the logistic model in these situations.

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Researchers should cite this work as follows:

Article Context

Resource Type
Differential Equation Type
Technique
Qualitative Analysis
Application Area
Course
Course Level
Lesson Length
Technology
Approach
Skills
Key Scientific Process Skills
Assessment Type
Vision and Change Core Competencies - Ability
Principles of How People Learn
Bloom's Cognitive Level

Description

We offer modeling opportunities in which (1) an artificial data set is given and a model is required and (2) several data sets from an historical protozoan study in the Soviet Union in the 1930's form the basis of the modeling and data. Several different approaches for estimating parameters are offered and the results from these approaches will be compared with each other as well as against the data itself.

Article Files

  • nb 1-018-Mma-T-LogisticPopModel-TeacherVersion.nb(NB)
  • pdf 1-018-Mma-T-LogisticPopModel-TeacherVersion.pdf(PDF)
  • pdf 1-018-S-LogisticPopModel-StudentVersion.pdf(PDF)
  • tex 1-018-S-LogisticPopModel-StudentVersion.tex(TEX)
  • pdf 1-018-T-LogisticPopModel-TeacherVersion.pdf(PDF)
  • tex 1-018-T-LogisticPopModel-TeacherVersion.tex(TEX)
  • eps 1-18-ModelingTwoLogDataGenPlot.eps(EPS)
  • png LogisticPic.png(PNG)
  • cls SIMIODE.cls(CLS)
  • jpg SimiodeLogo.jpg(JPG)
  • License terms

Authors

Author(s): Brian Winkel

SIMIODE - Systemic Initiative for Modeling Investigations and Opportunities with Differential Equations

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