Front

What is a Box-and-Whisker Plot?

Back

A Box-and-Whisker Plot is a graphical representation of a dataset that displays its minimum, first quartile (Q1), median, third quartile (Q3), and maximum values.

Tags

CCSS.6.SP.B.4

CCSS.HSS.ID.A.1

Front

What does the maximum value represent in a Box-and-Whisker Plot?

Back

The maximum value represents the highest data point in the dataset.

Tags

CCSS.6.SP.B.4

CCSS.HSS.ID.A.1

Front

What does the minimum value represent in a Box-and-Whisker Plot?

Back

The minimum value represents the lowest data point in the dataset.

Tags

CCSS.6.SP.B.4

CCSS.HSS.ID.A.1

Front

How is the median defined in a Box-and-Whisker Plot?

Back

The median is the middle value of the dataset when it is ordered from least to greatest.

Tags

CCSS.6.SP.B.4

CCSS.HSS.ID.A.1

Front

What is the significance of the upper quartile (Q3) in a Box-and-Whisker Plot?

Back

The upper quartile (Q3) is the median of the upper half of the dataset, representing the 75th percentile.

Tags

CCSS.6.SP.B.4

CCSS.HSS.ID.A.1

Front

What is the significance of the lower quartile (Q1) in a Box-and-Whisker Plot?

Back

The lower quartile (Q1) is the median of the lower half of the dataset, representing the 25th percentile.

Tags

CCSS.6.SP.B.4

CCSS.HSS.ID.A.1

Front

How do you calculate the interquartile range (IQR)?

Back

The interquartile range (IQR) is calculated by subtracting the lower quartile (Q1) from the upper quartile (Q3): IQR = Q3 - Q1.

Tags

CCSS.6.SP.B.5C

Front

What does the whisker represent in a Box-and-Whisker Plot?

Back

The whiskers extend from the quartiles to the minimum and maximum values, showing the range of the data.

Tags

CCSS.6.SP.B.4

CCSS.HSS.ID.A.1

Front

What is the purpose of a Box-and-Whisker Plot?

Back

The purpose of a Box-and-Whisker Plot is to summarize and visualize the distribution of a dataset, highlighting its central tendency and variability.

Tags

CCSS.6.SP.B.4

CCSS.HSS.ID.A.1

Front

How can you identify outliers using a Box-and-Whisker Plot?

Back

Outliers can be identified as data points that fall below Q1 - 1.5 * IQR or above Q3 + 1.5 * IQR.