This lesson covers the relationship between two quantitative variables using scatter plots. It begins with an explanation of categorical and quantitative variables, followed by a detailed look at scatter plots and their axes. The lesson explores different shapes that scatter plots can take, such as linear, quadratic, and exponential, and how these relate to function families. Examples include analyzing alligator length and weight data, and cricket chirps in relation to temperature, demonstrating how scatter plots help visualize data relationships.

Which of the following is an example of a categorical variable?

• Salary in dollars

• Hair color

• Number of siblings

• Temperature in degrees

What does a scatter plot typically represent?

• The relationship between two categorical variables

• The relationship between a categorical and a quantitative variable

• The relationship between multiple categorical variables

• The relationship between two quantitative variables

In a scatter plot, what does the X-axis typically represent?

• A categorical variable

• A quantitative variable

• A constant value

• A dependent variable

What shape might a scatter plot take if it fits a quadratic function?

• A straight line

• A parabola

• A circle

• A zigzag pattern

Which function family is likely to fit a scatter plot with a curved shape?

• Constant

• Logarithmic

• Quadratic

• Linear

Why might researchers prefer a linear model over other types of functions?

• Linear models require less data

• Linear models are easier to work with

• Linear models are more accurate

• Linear models are always the best fit

What relationship did researchers find between cricket chirps and temperature?

• Crickets chirp more in cooler weather

• Crickets chirp the same regardless of temperature

• Crickets chirp less in warmer weather

• Crickets chirp more in warmer weather