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Health v. Wealth -- International Data Analysis, Modeling & Correlation Project

Health v. Wealth -- International Data Analysis, Modeling & Correlation Project
Health v. Wealth -- International Data Analysis, Modeling & Correlation Project
Health v. Wealth -- International Data Analysis, Modeling & Correlation Project
Health v. Wealth -- International Data Analysis, Modeling & Correlation Project
Health v. Wealth -- International Data Analysis, Modeling & Correlation Project
Health v. Wealth -- International Data Analysis, Modeling & Correlation Project
Health v. Wealth -- International Data Analysis, Modeling & Correlation Project
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3 MB|44 pages
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Correlations and Causation should be abundantly clear when students examine data of the Health and Wealth of over 80 nations around the world. The world is everchanging and it is important for students to have a basic level of global awareness. In Health v. Wealth, students will use real world data to model regression functions, examine correlations and predict the future.

In this project students will investigate global data sets to examine potential correlations related with the Health and Wealth of nations. They will put their skills to the test serving as a statistician and representing a country at a Model UN simulation.

Students will use the skills of patterns, constructing pie graphs, regression functions for modeling and using their equations to make predictions. What makes a model strong? Students will explore this question.

This lesson is designed to work with a class set of TI graphing calculators and would work with an Advanced Algebra 1 class, Algebra 2 or PreCalculus.

In this 44 page document you will be given a mapping to the Content Standards, an outline for how to implement the project, handout resources for students to use, and an answer key. In all it is five different assignments which would span 1-2 weeks and work with a linear and exponential modeling unit --

A.) Students work in groups to analyze data of Underweight Children and correlate it with 11 other measures to see what is related across 42 countries

B.) Life Expectancy -- Is Linear Regression an accurate predictor or are other models needed? This assignment looks at the cost and benefits of using short-term and long-term data while analyzing life expectancy in 13 different topics. This activity aims to teach the value in short-term and long-term data approaches in terms of interpolation and extrapolation of data.

C.) Health v. Wealth -- The need for non-linear functions is on display in an analysis of Child Mortality rates and per capita GDP measurements. Students will use 5 different regression models and determine which best-fits the data.

D.) Model UN Country Research -- Students will research data for a country of their choice and create predictive models for 6 variables. This will likely need to be done in a computer lab.

E.) Model UN Country Simulation -- Splitting the class into two, they will serve the role of presenter and audience member. During these days presenters share the data and worldview of the nation of their choice.

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Total Pages
44 pages
Answer Key
Included
Teaching Duration
2 Weeks
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