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Title – Line Of Best Fit to Forecast Unemployment Rates
By – James Walsh
Primary Subject – Math
Secondary Subjects – Social Studies
Grade Level – 9-12
Standards Addressed:
Objective 3 Data Analysis and Probability – NC Competancy Goal 3.03
Create Linear Models for sets of data to solve problems.
General Goal:
Create a line of best fit using historical data for unemployment rates.
Specific Objectives:
Compare the difference between the observed unemployment rates recently and the expected rates based on a linear regression model. Discuss the causes leading to the difference, and discuss whether this trend will continue or return to expected levels.
Required Materials:
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TI-83 Plus Calculator (or similar)
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Internet access
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Historical chart of the unemployment rate over the last twenty years
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Graph Paper
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Microsoft Word 2003 or later.
Anticipatory Set (Lead-In):
Video of the presidential address on the state of the economy
Step-By-Step Procedures:
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Show video of presidential address.
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Gather historical data from the internet of the unemployment rate over the last 20 years (Bureau of Statistics).
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Using data, run a linear regression model.
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Compare the observed and expected rates over the last few years leading to the present year.
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Graph the differences between the observed and predicted on graph paper.
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Have students list five reasons why there is a difference and how it has affected them personally.
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Class discussion and sharing
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Using model predict the unemployment rates for the next few years. Discuss what changes in society would lower the unemployment rate back to historical levels.
Closure:
Ask students to list five other types of data one could use linear regression models to help solve problems or make predictions.
Assessment Based On Objectives:
Using one of the data types students chose, create a linear regression model, and explain how these can be used to solve problems in their own life.
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James Walsh
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