Box-and-Whisker Plot and Scatter Plot

Grade 9 · Mathematics

Semester 2 | Period 6 | Week 33

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Subject: Mathematics

Semester: 2

Period: 6

Week: 33

WEEK 33

Class: Grade 9
Age: 14 years
Duration: 40 minutes of 5 periods
Subject: Mathematics
Topic: Box-and-Whisker Plot & Scatter Plot
Focus: Constructing, Interpreting, and Analyzing Box-and-Whisker and Scatter Plots

SPECIFIC OBJECTIVES:

By the end of the lesson, pupils should be able to:

  1. Explain the components of a box-and-whisker plot (median, quartiles, interquartile range).
  2. Construct a box-and-whisker plot from a given data set.
  3. Interpret information from box-and-whisker plots.
  4. Plot pairs of values on a scatter plot.
  5. Identify trends and correlations (positive, negative, none) from scatter plots.
  6. Apply box-and-whisker and scatter plots to analyze real-life data.

 

INSTRUCTIONAL TECHNIQUES:

  • Question and answer
  • Guided demonstration
  • Practical exercises
  • Group work and discussion
  • Real-life data applications

 

INSTRUCTIONAL MATERIALS:

  • Graph paper
  • Rulers and pencils
  • Whiteboard and marker
  • Worksheets with data sets
  • Flashcards with numbers

 

PERIOD 1 & 2: Box-and-Whisker Plot

PRESENTATION:

Step

Teacher’s Activity

Pupil’s Activity

Step 1 – Anticipation (Warm-up)

Teacher presents a small data set and asks: “How can we summarize this data visually?”

Pupils suggest ways (table, chart, plot).

Step 2 – Building Knowledge (Explanation)

Introduces box-and-whisker plot. Explains key terms:

  • Median (middle value)
  • Lower quartile (Q1)
  • Upper quartile (Q3)
  • Interquartile range (IQR = Q3 – Q1)

Pupils listen and take notes.

Step 3 – Demonstration
  • Data: 12, 15, 18, 20, 22, 24, 27
  • Step 1: Order data
  • Step 2: Find median, Q1, Q3

Step 3: Draw box from Q1 to Q3, whiskers to min & max

Pupils observe and copy

Step 4 – Guided Practice

Teacher gives data set: 14, 16, 18, 19, 21, 23, 25

Pupils construct box-and-whisker plot.

 

Pupils work individually or in pairs, guided by teacher.

 

NOTE ON BOARD:

  • Box represents middle 50% of data.
  • Whiskers extend to minimum and maximum values.
  • IQR = Q3 – Q1 shows data spread.

EVALUATION (5 exercises):

  1. Construct a box-and-whisker plot for: 10, 12, 14, 16, 18, 20, 22.
  2. Find Q1, Q3, median, min, max for: 15, 17, 19, 20, 22, 25, 27.
  3. Calculate IQR for: 11, 13, 15, 17, 19, 21, 23.
  4. Draw box plot for: 5, 7, 9, 11, 13, 15.
  5. Interpret distribution for: 8, 10, 12, 14, 16, 18, 20.

CLASSWORK (5 questions):

  1. Construct box plot for: 12, 15, 17, 18, 20, 22.
  2. Identify median, Q1, Q3 for: 14, 16, 19, 20, 23, 25.
  3. Calculate IQR for: 10, 13, 15, 18, 21.
  4. Draw box-and-whisker plot for: 7, 9, 11, 13, 15.
  5. Interpret the data spread of: 8, 12, 15, 17, 19.

ASSIGNMENT (5 tasks):

  1. Construct box plot for student scores: 12, 14, 16, 18, 20, 22, 24.
  2. Calculate median, Q1, Q3, min, max.
  3. Find IQR for scores: 15, 17, 19, 21, 23.
  4. Interpret a box plot of class test scores.
  5. Write one real-life scenario where a box plot is useful.

 

PERIOD 3 & 4: Scatter Plot

PRESENTATION:

Step

Teacher’s Activity

Pupil’s Activity

Step 1 – Anticipation

Shows paired data (e.g., hours studied vs. marks obtained). Asks: “How can we show the relationship visually?”

Pupils suggest graph or chart.

Step 2 – Building Knowledge (Explanation)

Explains scatter plot: plotting pairs of values on a coordinate plane (x, y). Introduces correlations:

  • Positive correlation: as x increases, y increases
  • Negative correlation: as x increases, y decreases
  • No correlation: no clear trend

Pupils take notes.

Step 3 – Demonstration
  • Example: (1, 2), (2, 4), (3, 6), (4, 8)
  • Plot points on graph
  • Draw trend line
  • Identify correlation: positive

Pupils observe and copy.

Step 4 – Guided Practice

Data: Hours studied: 1, 2, 3, 4, 5; Marks: 50, 55, 60, 65, 70

  • Pupils plot points
  • Identify trend

 

Pupils plot and discuss in pairs.

NOTE ON BOARD:

  • Scatter plots show relationships between two variables.
  • Trend lines help identify correlation type.
  • Useful in real-life analysis (study time vs. performance, height vs. weight).

EVALUATION (5 exercises):

  1. Plot points: (2,3), (4,6), (6,9), (8,12). Identify correlation.
  2. Hours slept vs. exam scores: plot and describe trend: (5,50), (6,55), (7,60), (8,65).
  3. Plot: (1,2), (2,3), (3,5), (4,7). Identify type of correlation.
  4. Find if height vs. weight data shows positive, negative, or no correlation: (150,45), (155,50), (160,55), (165,60).
  5. Plot number of hours exercising vs. calories burned: (1,200), (2,400), (3,600), (4,800).

CLASSWORK (5 questions):

  1. Plot data: x = 1,2,3,4,5; y = 2,4,6,8,10. Identify correlation.
  2. Study hours vs. marks: (2,40), (3,50), (4,60), (5,70). Plot and interpret.
  3. Temperature vs. ice cream sales: (20,50), (25,60), (30,70), (35,80). Plot points.
  4. Plot weight vs. height: (50,150), (55,155), (60,160), (65,165). Identify correlation.
  5. Study time vs. sleep hours: plot data and determine correlation.

ASSIGNMENT (5 tasks):

  1. Collect paired data from classmates (e.g., hours studying vs. marks) and plot a scatter plot.
  2. Identify correlation type in the data you collected.
  3. Plot a scatter graph for daily temperature vs. electricity consumption in a week.
  4. Find a real-life scenario, collect data, and create a scatter plot.
  5. Write a short paragraph interpreting your scatter plot’s trend.