General Professional Knowledge (Essential Professional Skills, Literacy & Numeracy)

Statistics and Probability are branches of mathematics that help us organize, analyze, and interpret data.

  • Statistics: deals with collecting, organizing, presenting, analyzing, and interpreting data.
  • Probability: deals with measuring the likelihood of events occurring.

These concepts are vital for teachers because they are used in:

  • Classroom assessment
  • Research on learners’ performance
  • Decision-making about interventions

1. Data Collection and Representation

Definition

  • Data: Facts, figures, or measurements collected for analysis.
  • Data collection: Gathering information using surveys, observations, experiments, or measurements.

Types of Data

  1. Primary data – collected directly (e.g., measuring students’ height)
  2. Secondary data – already existing (e.g., school records)

Representation of Data

  • Tabular form (tables)
  • Graphical form:
    • Bar graphs
    • Pie charts
    • Pictograms
    • Line graphs
    • Histograms

Example 1: Survey of favorite fruits in a class of 30 students

Fruit Frequency
Mango 10
Banana 5
Orange 8
Apple 7

This is tabular representation.

Example 2: Draw a bar graph from the table above

  • X-axis: Fruits
  • Y-axis: Number of students

Example 3: Represent the data using a pie chart

  • Total students = 30
  • Mango: 10/30 × 360° = 120°
  • Banana: 5/30 × 360° = 60°
  • Orange: 8/30 × 360° = 96°
  • Apple: 7/30 × 360° = 84°

Example 4: Using pictogram (1 🍎 = 2 students)

  • Mango: 5 icons, Banana: 2.5 ≈ 3 icons, etc.

Example 5: Line graph representing student scores in Maths over 5 weeks

Week Score
1 40
2 45
3 50
4 55
5 60

Plot week on X-axis, score on Y-axis, join points.

2. Graph Interpretation

Definition

Interpreting graphs involves reading information, comparing values, and drawing conclusions from tables or graphs.

Steps

  1. Identify title, axes, and units.
  2. Check the scale of the graph.
  3. Observe trends or patterns.
  4. Answer questions such as:
    • Which category has the highest/lowest value?
    • What is the difference between categories?

Examples

  • Example 1: Bar graph of students’ scores: Scores: A: 50, B: 60, C: 55, D: 70 → D scored the highest, B second highest.
  • Example 2: Line graph of rainfall over 6 months: Highest rainfall in June, lowest in January.
  • Example 3: Pie chart of expenditure: Rent 50%, Food 30%, Savings 20% → Most money spent on rent.
  • Example 4: Histogram showing test scores: Mode = highest bar
  • Example 5: Compare two bar graphs of boys’ vs girls’ scores → Girls perform slightly better in Maths than boys.

3. Mean, Median, Mode

Definitions

  1. Mean (Average)
    • Sum of all observations ÷ Number of observations
    • Formula: Mean = ΣX / n
  2. Median
    • Middle value when data is arranged in ascending order
    • If n is odd → middle value
    • If n is even → average of two middle values
  3. Mode
    • Value that occurs most frequently

Examples

  • Example 1: 4, 6, 8, 10, 12 → Mean = 8, Median = 8, Mode = None
  • Example 2: 5, 7, 5, 9, 10 → Mean = 7.2, Median = 7, Mode = 5
  • Example 3: 3, 8, 12, 8, 15, 8 → Mean = 9, Median = 8, Mode = 8
  • Example 4: 20, 25, 30, 35, 40 → Mean = 30, Median = 30, Mode = None
  • Example 5: 1, 2, 2, 2, 3, 4, 4 → Mean ≈ 2.57, Median = 2, Mode = 2

4. Range and Standard Deviation

Range

Difference between largest and smallest values

Formula: Range = Maximum value - Minimum value

Examples

  • 5, 8, 12 → Range = 7
  • 10, 15, 20, 25 → Range = 15
  • 3, 6, 9, 12, 15 → Range = 12
  • 7, 14, 21 → Range = 14
  • 2, 5, 11, 19 → Range = 17

Standard Deviation (SD)

Measure of how spread out the numbers are from the mean

Formula: SD = √(Σ(Xi - X̄)² / n) where Xi = individual values, X̄ = mean, n = number of values

Examples

  • Data: 2, 4, 6, 8 → SD ≈ 2.236
  • 1, 3, 5, 7, 9 → SD ≈ 2.828
  • 10, 12, 14, 16 → SD ≈ 2.236
  • 5, 7, 7, 9 → SD ≈ 1.414
  • 6, 8, 10, 12, 14 → SD ≈ 2.828

5. Probability of Events

Definition

  • Probability measures the likelihood of an event occurring.
  • Probability values range: 0 ≤ P(E) ≤ 1
  • Formula: P(E) = Number of favorable outcomes / Total number of outcomes

Examples

  • Toss a coin. Probability of Heads → 1/2
  • Roll a dice. Probability of 6 → 1/6
  • Draw a red card from a deck → 26/52 = 1/2
  • Choose a number 1–10. Probability of even number → 5/10 = 1/2
  • Toss 2 coins. Probability of both heads → 1/4