Weight a Minute (Updated!)

How realistic are extreme weight-loss competitions?

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Weight a Minute (Updated!)

How realistic are extreme weight-loss competitions?

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Check it out! This lesson was just updated in September 2024, and we hope you love the new and improved version. If you've already prepped an earlier version, fear not, you can still find those here through Thursday December 5, 2024.

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2023-2024 Versions

In the fall of 2024, Citizen Math released updated versions of every lesson in our library, plus a few new ones! We know you may have already prepped an earlier version or planned a repeat of last year, so we're continuing to make these earlier versions available through Thursday December 5, 2024.

You can find the new lessons through the regular search, and we hope you love them as much as we do. You can read more about these updates in Our Community.

Who should win extreme weight loss competitions? In the TV game show The Biggest Loser, contestants compete to lose the greatest percent of body weight. While some praised the show as a helpful source of inspiration, others criticized it as an unrealistic and unhealthy example of how to lose weight.

In this lesson, students use linear functions and lines-of-best-fit to predict results from Season 8 of The Biggest Loser and discuss whether such examples of extreme weight loss are realistic and sustainable.

REAL WORLD TAKEAWAYS

  • Contests such as The Biggest Loser challenge contestants to lose an extreme amount weight in a short amount of time.
  • According to doctors, it can be unhealthy (and unsustainable) to attempt to lose more than two pounds per week.
  • Shows like The Biggest Loser do not present a realistic depiction of healthy weight loss.

MATH OBJECTIVES

  • Create and interpret scatterplots of data describing a real-world situation
  • Estimate a line of best fit through a scatterplot; interpret the slope and y-intercept of the line; use the line to make predictions
  • Explain why having more data improves the reliability of a line-of-best-fit for making predictions

Appropriate most times as students are developing conceptual understanding.
Grade 8
Functions
Grade 8
Functions
Content Standards 8.SP.1 Construct and interpret scatter plots for bivariate measurement data to investigate patterns of association between two quantities. Describe patterns such as clustering, outliers, positive or negative association, linear association, and nonlinear association. 8.SP.2 Know that straight lines are widely used to model relationships between two quantitative variables. For scatter plots that suggest a linear association, informally fit a straight line, and informally assess the model fit by judging the closeness of the data points to the line. 8.SP.3 Use the equation of a linear model to solve problems in the context of bivariate measurement data, interpreting the slope and intercept. For example, in a linear model for a biology experiment, interpret a slope of 1.5 cm/hr as meaning that an additional hour of sunlight each day is associated with an additional 1.5 cm in mature plant height.
Mathematical Practices MP.3 Construct viable arguments and critique the reasoning of others. MP.4 Model with mathematics.

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