Analyzing Variability in Data

This video tutorial covers the use of box plots to analyze data distributions. It includes examples of height distributions among athletes, response times for emergency calls, pineapple weights in crates, and viewer ages for TV shows. The tutorial explains concepts like median, interquartile range (IQR), and variability, helping students understand how to interpret and compare data using box plots.

Which two sports have the most similar height distributions among players?

• Football and Hockey

• Hockey and Baseball

• Basketball and Football

• Basketball and Baseball

Which sport shows the greatest variability in players' heights?

• Hockey

• Football

• Basketball

• Baseball

What percentage of the fire department's response times were under 13 minutes?

• 75%

• 60%

• 50%

• 90%

Which statement is true about the fire department's response times?

• More than half were over 13 minutes.

• Fewer than 30% were over 13 minutes.

• Half were exactly 11 minutes.

• All were under 9 minutes.

Which crate had the most variable pineapple weights?

• Crate 3

• All crates had the same variability

• Crate 1

• Crate 2

Where was the heaviest pineapple found?

• Crate 2

• Crate 1

• All crates had the same heaviest weight

• Crate 3

Which crate had the greatest median weight?

• Crate 1

• All crates had the same median weight

• Crate 2

• Crate 3

Which TV show is a sixth grader more likely to watch based on age variability?

• Neither show

• Both shows equally

• The show with a mean age of 30 and MAD of 5

• The show with a mean age of 35 and MAD of 20

What does a higher MAD indicate about a TV show's viewer ages?

• Exact same ages

• No variability

• More variability

• Less variability

If a show's mean age is 30 with a MAD of 5, what can be inferred?

• Most viewers are exactly 30

• Ages are tightly clustered around 30

• Ages vary widely from 30

• All viewers are under 30