Math 8 Lesson: Box Plots
Here are the birth weights, in ounces, of all the puppies born at a kennel in the past month.
13 14 15 15 16 16 16 16 17 17 17 17 17 17 17 18 18 18 18 18 18 18 18 19 20[br][br]What do you notice and wonder about the distribution of the puppy weights?
Twenty people participated in a study about blinking. The number of times each person blinked while watching a video for one minute was recorded. The data values are shown here, in order from smallest to largest.
3 6 8 11 11 13 14 14 14 14 16 18 20 20 20 22 24 32 36 51
Use the grid and axis to make a boxplot of this data set.
Find the median (Q2) and mark its location.[br]Find the first quartile (Q1) and the third quartile (Q3). Mark their locations.[br][br]A[b] box plot[/b] can be used to represent the five-number summary graphically. Let’s draw a box plot for the number-of-blinks data. [br][br][list][*]Draw a box that extends from the first quartile (Q1) to the third quartile (Q3). Label the quartiles.[/*][*]At the median (Q2), draw a vertical line from the top of the box to the bottom of the box. Label the median.[/*][*]From the left side of the box (Q1), draw a horizontal line (a whisker) that extends to the minimum of the data set. On the right side of the box (Q3), draw a similar line that extends to the maximum of the data set.[/*][/list]
What are the minimum and maximum values?
You have now created a box plot to represent the number of blinks data. What percentage of the data values are represented by each of these elements of the box plot?
The left whisker[br]
The box
The right whisker
Suppose there were some errors in the data set: the smallest value should have been 6 instead of 3, and the largest value should have been 41 instead of 51. Determine if any part of the five-number summary would change. If you think so, describe how it would change. If not, explain how you know.
Math 8 Practice: Box Plots
Each student in a class recorded how many books they read during the summer. Here is a box plot that summarizes their data.ing the summer. Here is a box plot that summarizes their data.
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[/img][br][br]What is the greatest number of books read by a student in this group?
What is the median number of books read by the students?
What is the interquartile range (IQR)?
Use this five-number summary to draw a box plot. All values are in seconds. Minimum: 40, First quartile (Q1): 45, Median: 48, Third quartile (Q3): 50, Maximum: 60.
The data shows the number of hours per week that each of 13 seventh-grade students spent doing homework. 3, 10, 12, 4, 7, 9, 5, 5, 11, 11, 5, 12, 11. Create a box plot to summarize the data.
The box plot displays the data on the response times of 100 mice to seeing a flash of light. How many mice are represented by the rectangle between 0.5 and 1 second?
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[/img]