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This lesson forecasts unemployment rates using a linear regression model and a graphing calculator
9, 10, 11, 12
Title – Line Of Best Fit to Forecast Unemployment Rates
By – James Walsh
Primary Subject – Math
Secondary Subjects – Social Studies
Grade Level – 9-12
- Objective 3 Data Analysis and Probability – NC Competancy Goal 3.03
- Create Linear Models for sets of data to solve problems.
- Create a line of best fit using historical data for unemployment rates.
- 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.
- TI-83 Plus Calculator (or similar)
- Internet access
- Historical chart of the unemployment rate over the last twenty years
- Graph Paper
- Microsoft Word 2003 or later.
Anticipatory Set (Lead-In):
- Video of the presidential address on the state of the economy
- Show video of presidential address.
- Gather historical data from the internet of the unemployment rate over the last 20 years (Bureau of Statistics).
- Using data, run a linear regression model.
- Compare the observed and expected rates over the last few years leading to the present year.
- Graph the differences between the observed and predicted on graph paper.
- Have students list five reasons why there is a difference and how it has affected them personally.
- Class discussion and sharing
- 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.
- 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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