Interpreting Scatter Plots

What is a scatter plot?

• A graph that shows the relationship of two data sets.
• A graph drawn using rectangular bars to show how large each value is.
• A graph that shows information that is connected in some way.
• A graph that shows data changing over time.

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Which relationship could be represented by this scatter plot?

• As the number of muffins in a box increases, the price increases.

• As the speed of a car increases, the distance the car travels increases.

• As the population of a city increases, the number of schools in the

  city increases.

• As the number of daylight hours increases, the number of night hours decreases.

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Imagine Avery and Grace are looking at a scatterplot that seems to have no association. What does this mean for the scatterplot?

• ...it has no ordered pairs

• ...it has ordered pairs that have a negative pattern

• ...its ordered pairs have no predictable pattern

• ...if it makes a lion on a graph (roar!)

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Ethan and Isla are analyzing a scatter plot of their running times versus training hours. What type of correlation does this scatter plot show?

• positive linear association

• negative linear association

• no association

• nonlinear association

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As the age of the car increases, its value decreases. Which scatterplot represents this relationship?

• A
• B
• C
• D

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Label the type of association shown by the scatter plot as positive, negative or none.

• positive

• negative

• none

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Label the type of association shown by the scatter plot as positive, negative or none.

• positive

• negative

• none

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Which best describes the association shown in the scatter plot below?

• Negative and linear

• Negative and non-linear

• Positive and linear

• Positive and non-linear

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Given the following Scatter Plot, select the option that is most likely the r value.

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Aiden and Anika are exploring the world of data! They stumbled upon a scatter plot filled with mysterious dots. Can you help them figure out the correlation?

• Weak Positive

• No Correlation

• Strong Negative

• Weak Negative

• Strong Positive

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