What’s the best way to use Instagram? When a user posts an image to Instagram, they often obsess over how many likes and comments it receives. However, it can be hard to know what strategies users can take to make their pictures more popular.
In this lesson, students use histograms, linear regressions, and r-squared values to debate the most effective strategies to gain Insta-fame...and the consequences of always having to smile for the camera.
Students will
Interpret the slope and intercept of a linear model in the context of the data
Compare R2 values
Distinguish between correlation and causation
Before you begin
Students will interpret R-squared values in this lesson. If they aren't already familiar with that concept, you'll want to build in time to introduce it.
How have video game consoles changed over time? Students create exponential models to predict the speed of video game processors over time, compare their predictions to observed speeds, and consider the consequences as digital simulations become increasingly lifelike.
Topic:
Building Functions (BF), Interpreting Categorical and Quantitative Data (ID), Interpreting Functions (IF), Linear, Quadratic, and Exponential Models (LE), Seeing Structure in Expressions (SSE)
Can you predict a country's Winter Olympic performance? Students analyze scatterplots and correlation coefficients to pick out the best predictive model for Olympic success.
Topic:
Interpreting Categorical and Quantitative Data (ID)
What makes for happy countries? Students interpret lines of best fit and correlation coefficients to determine what types of policy changes are most likely to positively impact a country’s well-being.
Topic:
Interpreting Categorical and Quantitative Data (ID)
How have temperatures changed around the world? Students use periodic functions to compare long-term average monthly temperatures to recorded monthly temperatures, evaluate evidence of climate change, and discuss possible consequences.
Topic:
Functions (F), Interpreting Categorical and Quantitative Data (ID), Interpreting Functions (IF)
How should pro sports teams spend their money? Students use linear regressions and r-squared values to analyze data from professional sports leagues, evaluate how various factors correlate with wins, and debate whether a higher payroll is good business strategy.
Topic:
Interpreting Categorical and Quantitative Data (ID)
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Mathalicious lessons provide teachers with an opportunity to teach standards-based math through real-world topics that students care about.
How have video game consoles changed over time? Students create exponential models to predict the speed of video game processors over time, compare their predictions to observed speeds, and consider the consequences as digital simulations become increasingly lifelike.
Topic:
Building Functions (BF), Interpreting Categorical and Quantitative Data (ID), Interpreting Functions (IF), Linear, Quadratic, and Exponential Models (LE), Seeing Structure in Expressions (SSE)