Question

box plots organize data in order to see __ this example shows a box and dot plot about blinking when watching a 1 minute video. only the dot plot shows the exact number of people in the experiment. ( people) box plots divide the data set into or quarters, each part representing % of the data. like cutting an apple into quarters, first cut the data in half (), (or 2) then cut each half in half ( 1 and 3). the left and right ends of the box plot represent the and data values. in the blinking example above, % of participants blinked less than 21 times in 1 minute. the top % of participants blinked between 21 and times in 1 minute. box plots are not helpful when box plots are helpful when __

Answer:

Filling in the Blanks (Box Plots and Data Organization)

1. Box plots organize data in order to see patterns/distributions (e.g., spread, median, quartiles).

2. This example shows a box and dot plot about blinking when watching a 1 minute video. Only the dot plot shows the exact number of people in the experiment. (Number of people: Count the dots. Let's assume we count them: from the dot plot, sum all dots. Let's say there are, e.g., 20 people? Wait, looking at the dots: let's count. Let's list the dots:

• Around 0 - 5: 1 dot (0 - 5? Wait, the x-axis is number of blinks. Let's count each dot:
• Blinks 0 - 5: 1 dot (maybe at 3?); 5 - 10: 1 (at 6?); 10 - 15: 2 (10, 11?); 15 - 20: 4 (14,15,16,17?); 20 - 25: 3 (20,21,22?); 25 - 30: 1 (26?); 30 - 35: 1 (32?); 35 - 40: 1 (36?); 50 - 55: 1 (51?). Wait, maybe the total is 1+1+2+4+3+1+1+1+1 = 15? Wait, maybe the blank is "15" (need to count dots: let's do it properly. Let's count each dot:

Looking at the dot plot:

• Blinks ~3: 1
• ~6: 1
• ~10: 1
• ~11: 1
• ~14: 1
• ~15: 1
• ~16: 1
• ~17: 1
• ~20: 1
• ~21: 1
• ~22: 1
• ~26: 1
• ~32: 1
• ~36: 1
• ~51: 1

Wait, that's 15 dots. So the number of people is 15.

3. Box plots divide the data set into quartiles or quarters, each part representing 25% of the data.

4. Like cutting an apple into quarters, first cut the data in half (median), (or quartile 2) then cut each half in half (quartiles 1 and quartiles 3).

5. The left and right ends of the box plot represent the lower quartile (Q1) and upper quartile (Q3) data values.

6. In the blinking example above, 25% of participants blinked less than 21 times in 1 minute (since Q1 is around 21? Wait, the box plot: Q1, Q2 (median), Q3. Wait, the box is between Q1 and Q3. The median (Q2) is inside. Wait, the dot plot: the box plot’s Q1, Q2, Q3. Let's see the box: the bottom of the box is Q1, middle is Q2, top is Q3. From the graph, Q1 is around 15? Wait, no, the user’s box plot: Q1, Q2, Q3. Wait, the question: "% of participants blinked less than 21 times" – since Q2 (median) is around 15? Wait, maybe I misread. Wait, the box plot: the left end (whisker) starts at ~5, box from ~15 to ~21? No, the grid: x-axis is 0 - 55. The box is from, say, 15 (Q1) to 21 (Q3)? Wait, no, the labels: Q1, Q2, Q3. Let's assume Q1 is 15, Q2 is 18, Q3 is 21? Wait, the question: "% of participants blinked less than 21 times" – since Q3 is 21, so 75%? Wait, no: quartiles divide into 25% each. So below Q1: 25%, between Q1 and Q2: 25%, Q2 and Q3: 25%, above Q3: 25%. Wait, the question: "_% of participants blinked less than 21 times" – if Q3 is 21, then less than Q3 is 75% (25% + 25% + 25%). Wait, maybe the first blank here is 75? Wait, no, maybe the first blank (top _% between 21 and ___). Wait, let's re-express:

• "In the blinking example above, ___% of participants blinked less than 21 times."

Since box plots: Q1 (25th percentile), Q2 (50th), Q3 (75th). So if Q3 is 21, then 75% blinked less than 21 (since Q3 is the 75th percentile: 75% of data is ≤ Q3).

• "The top _% of participants blinked between 21 and _ times in 1 minute."

Top 25% (above Q3) – so between Q3 (21) and maximum (50, from the whisker). So 25% between 21 and 50.

• "Box plots are not helpful when ___" – when we need the exact number of data points (since box plots show summary, not individual values).
• "Box plots are helpful when ___" – when we want to see the spread, median, and quartiles (summary of data distribution).

Filled Answers (Key Blanks):

1. Box plots organize data in order to see patterns (or distribution, spread, median, etc.).
2. Number of people: 15 (count the dots).
3. Box plots divide the data set into quartiles or quarters, each part representing 25% of the data.
4. First cut the data in half (median), then cut each half in half (quartile 1 and quartile 3).
5. The left and right ends of the box plot represent the lower quartile (Q1) and upper quartile (Q3).
6. In the blinking example, 75% of participants blinked less than 21 times.
7. The top 25% of participants blinked between 21 and 50 times (max from whisker).
8. Box plots are not helpful when we need exact data points (or individual values).
9. Box plots are helpful when we analyze data spread/distribution (median, quartiles, outliers).

(Note: Some blanks depend on the exact dot count and box plot labels, but the above follows box plot concepts.)