1-170-CensusModeling-ModelingScenario

Gary William Epp; Jean Marie Linhart; Gary William Epp; Jean Marie Linhart; Gary William Epp; Jean Marie Linhart

doi:10.25334/MB13-B278

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1-170-CensusModeling-ModelingScenario

Author(s): Gary William Epp¹, Jean Marie Linhart

Central Washington University, Ellensburg WA USA

Keywords: logistic growth exponential population U.S. Census Data assumption Google Sheets Unites States Guatemala

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Abstract

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.

Citation

Researchers should cite this work as follows:

Epp, G. W., Jean Marie Linhart (2022). 1-170-CensusModeling-ModelingScenario. SIMIODE, QUBES Educational Resources. doi:10.25334/MB13-B278
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Article Context

Resource Type

Modeling Scenario

Differential Equation Type

Technique

Initial Value Problems

Qualitative Analysis

Application Area

Course

Course Level

Key Scientific Process Skills

Assessment Type

Pedagogical Approaches

Guided inquiry/investigation

Vision and Change Core Competencies - Ability

Principles of How People Learn

Bloom's Cognitive Level

Application & Analysis

Description

We will compare and contrast the United States census data and the Guatemala census data, and how these two datasets fulfill or fail to fulfill the modeling assumptions of the exponential and logistic models. Along the way, we will introduce the concept of the per capita population growth rate, and calculate the per capita population growth rate for the exponential model, the logistic model, and estimate the per capita population growth rate from the two census datasets.