To determine whether each statement about the data distributions is true or false, we would need to analyze the dot plots for both the volleyball and basketball teams. However, since I cannot see the plots, I can guide you through how to evaluate these statements based on typical characteristics of data distributions.
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There appears to be more variability in the volleyball data.
- True or False?: Look for the spread of the heights in the volleyball data compared to the basketball data. If the volleyball heights are more spread out (wider range, more outliers), then this statement is true; if they are more clustered together, then it is false.
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The mean absolute deviation is likely greater for volleyball than basketball.
- True or False?: The mean absolute deviation (MAD) measures how spread out the data is around the mean. If the volleyball data has more variability (as established in the first question), then this statement would be true. If the volleyball data is less variable than basketball, then it would be false.
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The mean height is likely greater for basketball players than for volleyball players.
- True or False?: Compare the average heights from the two dot plots. If the basketball players tend to be taller overall (e.g., if the dots representing their heights are consistently at higher levels than the volleyball players), this statement is true. If volleyball players are taller on average, then it would be false.
Once you assess the plots with these guidelines in mind, you can accurately categorize each statement as true or false.