sampling techniques
4 detailed 50-minute lessons with teaching scripts, worked examples, parent guides, and assessment criteria.
Lesson Overview
Total Lessons: 4
Tier: Foundation and Higher
Duration: 50 minutes per lesson (200 minutes total)
Exam Boards: AQA, Edexcel, OCR, Eduqas, CCEA
Tier: Foundation and Higher
Duration: 50 minutes per lesson (200 minutes total)
Exam Boards: AQA, Edexcel, OCR, Eduqas, CCEA
Learning Objectives
- Explain the key ideas of sampling techniques
- Apply sampling techniques to exam-style questions
- Develop independent study skills
- Build cross-topic connections
Prerequisites
- Read the revision notes for sampling techniques first (GCSE Revise summary)
- Key vocab to pre-teach: key terms from sampling techniques
- Basic skills: reading the summary notes and answering the practice questions there
Materials & Equipment
- Exercise book, pencil, ruler
- Scientific calculator
- Graph paper and squared paper
- Printed data tables (link below)
Lesson 1: Introduction: sampling techniques
Duration: 50 minutes
Starter Activity (5 minutes)
Quick Recall
Write down everything you already know about sampling techniques. Then check against the key terms: key terms from sampling techniques. Use a mini-whiteboard or paper.
Main Content (35 minutes)
Parent/Teacher Guide:
Before lesson: Read the script below. Pre-teach key vocab: key terms from sampling techniques.
If stuck: Re-read the revision notes (link above), then break the content into smaller steps.
Extension: See the Stretch & Challenge ideas in Lesson 4.
Before lesson: Read the script below. Pre-teach key vocab: key terms from sampling techniques.
If stuck: Re-read the revision notes (link above), then break the content into smaller steps.
Extension: See the Stretch & Challenge ideas in Lesson 4.
Teaching Script (35 mins):
Mins 0-5 - Hook: "Today: sampling techniques. By the end you will be able to answer exam questions on it unaided. It connects to the rest of Statistics because the ideas here recur across the spec."
Mins 5-20 - Direct Instruction: Work through the core ideas below one at a time; after each, ask your student to explain it back in their own words.
Mins 20-30 - Guided Practice: Model the worked example together, then let your student attempt the first practice question with guidance.
Mins 30-35 - Independent Practice: 2-3 practice questions from Lesson 3 below, with immediate feedback.
Mins 0-5 - Hook: "Today: sampling techniques. By the end you will be able to answer exam questions on it unaided. It connects to the rest of Statistics because the ideas here recur across the spec."
Mins 5-20 - Direct Instruction: Work through the core ideas below one at a time; after each, ask your student to explain it back in their own words.
Mins 20-30 - Guided Practice: Model the worked example together, then let your student attempt the first practice question with guidance.
Mins 30-35 - Independent Practice: 2-3 practice questions from Lesson 3 below, with immediate feedback.
First Look
Start with the revision notes summary, then attempt: explain the key ideas of sampling techniques
Plenary (5 minutes)
Check Out
Your student states one thing they learned and one question they still have about sampling techniques.
Lesson 2: Core Concepts: sampling techniques
Duration: 50 minutes
Starter Activity (5 minutes)
Review Previous Lesson
Quick recap: write 3 key points from Lesson 1 on sampling techniques. Check them against the notes below.
Main Content (35 minutes)
Key Fact: A population is the entire group being studied; a sample is a subset of the population.
Key Fact: Sampling is used when studying the whole population is impractical due to time, cost or access.
Key Fact: A random sample gives every member of the population an equal chance of being selected.
Key Fact: Random sampling can be done using random number tables, calculators or computers.
Key Fact: Systematic sampling selects every kth item from a list after a random start (k = population size ÷ sample size).
Key Fact: Stratified sampling divides the population into subgroups (strata) and samples proportionally from each stratum.
Practice (10 minutes)
Q: explain the key ideas of sampling techniques
Answer:
Plenary (5 minutes)
Explain Back
Your student teaches the key points back to you without looking. Fill any gaps immediately.
Lesson 3: Application: sampling techniques
Duration: 50 minutes
Starter Activity (5 minutes)
Quick Recall
Recall the key terms: key terms from sampling techniques. Define each in one sentence.
Main Content (35 minutes)
Parent/Teacher Guide: Let your student attempt each question alone first, then compare with the model answer. Award method marks for correct working even if the final answer is wrong.
Work through the practice questions on the revision notes page for this topic.
Plenary (5 minutes)
Error Review
Review any questions answered incorrectly. Identify whether the error was knowledge, method, or reading the question.
Lesson 4: Exam Practice: sampling techniques
Duration: 50 minutes
Starter Activity (5 minutes)
Command Words
Review what these command words require: state (one point), describe (say what happens), explain (say why), compare (both sides), evaluate (judgement).
Main Content (35 minutes)
Extended Answer
Extended question: Full-Mark Response A school has 120 boys and 180 girls. A stratified sample of 50 students is required. Calculate how many boys and how many girls should be sampled. Explain why stratified sampling is better than simple random sampling here. <div class="
Total students = 120 + 180 = 300. Boys: (120 ÷ 300) × 50 = 0.4 × 50 = 20 boys. Girls: (180 ÷ 300) × 50 = 0.6 × 50 = 30 girls. Stratified sampling is better than simple random sampling because it guarantees the sample reflects the gender balance of the population (40% boys, 60% girls). A simple random sample might by chance include too many or too few of one gender, giving a sample that does not represent the population accurately.
Exam Tips: Show your working for stratified sample calculations — the formula is frequently examined. | Round stratified sample sizes to whole numbers and check they sum to the total sample size. | When evaluating a sampling method, always comment on whether it is likely to be biased. | Systematic sampling requires an ordered list (sampling frame) — mention this. | Cluster sampling studies all members of selected clusters — it is different from stratified sampling.
Common Errors: ✗ Using the word 'random' to mean 'any' or 'arbitrary' ✓ Random means every member has an equal chance — it requires a proper random method like random numbers. ✗ Not rounding stratified sample sizes to whole numbers ✓ Sample sizes must be whole numbers — round to the nearest integer and check the total adds up. ✗ Confusing stratified and quota sampling ✓ Stratified sampling selects randomly within each stratum; quota sampling does not use random selection within each group. ✗ Forgetting that systematic sampling needs a random start ✓ The starting point must be chosen randomly between 1 and k; otherwise the sample may be biased.
Stretch & Challenge (Grade 8-9):
- Synoptic links: explain how sampling techniques connects to another Statistics topic you have studied
- Real-world: research one real-world use or example of sampling techniques
- Critical: "What are the limitations of the models used in sampling techniques?"
Plenary (5 minutes)
Assessment Criteria
- Got it: Confident explanation + correct worked examples
- Getting there: Main points OK, needs support with detail
- Not yet: Confused on key concepts - re-run Lesson 2
Homework & Consolidation
- Consolidation: Re-answer any Lesson 3 practice questions answered incorrectly (20 mins)
- Retrieval: Write flashcards for the key terms: key terms from sampling techniques (10 mins)
- Exam practice: One past-paper question on sampling techniques from the board websites (15 mins)
- Extension: Explain sampling techniques to someone else in your own words (10 mins)