s1 sampling
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 s1 sampling
- Apply s1 sampling to exam-style questions
- Develop independent study skills
- Build cross-topic connections
Prerequisites
- Read the revision notes for s1 sampling first (GCSE Revise summary)
- Key vocab to pre-teach: key terms from s1 sampling
- 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: s1 sampling
Duration: 50 minutes
Starter Activity (5 minutes)
Quick Recall
Write down everything you already know about s1 sampling. Then check against the key terms: key terms from s1 sampling. 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 s1 sampling.
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 s1 sampling.
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: s1 sampling. 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: s1 sampling. 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: Define what is meant by a "population" in statistics.
Plenary (5 minutes)
Check Out
Your student states one thing they learned and one question they still have about s1 sampling.
Lesson 2: Core Concepts: s1 sampling
Duration: 50 minutes
Starter Activity (5 minutes)
Review Previous Lesson
Quick recap: write 3 key points from Lesson 1 on s1 sampling. Check them against the notes below.
Main Content (35 minutes)
Definition: A sample is a smaller group selected from a larger population. We use samples to make inferences (educated guesses) about the whole population.
Important: A larger sample size generally gives more accurate results, but the method of sampling is equally important.
| Item | Detail |
|---|---|
| Population | The entire group being studied |
| Sample | A smaller group taken from the population |
| Inference | Using sample data to draw conclusions about the population |
| Bias | When the sample doesn't fairly represent the population |
| Representative | A sample that accurately reflects the population |
Practice (10 minutes)
Q: Define what is meant by a "population" in statistics.
Answer: The population is the entire group being studied or about which conclusions are to be drawn.
Plenary (5 minutes)
Explain Back
Your student teaches the key points back to you without looking. Fill any gaps immediately.
Lesson 3: Application: s1 sampling
Duration: 50 minutes
Starter Activity (5 minutes)
Quick Recall
Recall the key terms: key terms from s1 sampling. 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.
Q1: Define what is meant by a "population" in statistics.
Answer: The population is the entire group being studied or about which conclusions are to be drawn.
Q2: A school has 120 boys and 180 girls. A stratified sample of 50 students is needed. How many boys and girls should be selected?
Answer: Boys: (120/300) × 50 = 20; Girls: (180/300) × 50 = 30
Q3: A researcher wants to survey 25 people from a list of 200 using systematic sampling. What value of k should be used?
Answer: k = 200 ÷ 25 = 8 (select every 8th person)
Q4: Explain why asking people leaving a cinema about their views on films might produce a biased sample.
Answer: Biased because: only people who choose to watch films are surveyed; those leaving cinemas are likely to enjoy films more than general population; excludes people who don't go to cinemas.
Q5: Give two advantages of using a sample rather than surveying the whole population.
Answer: Any two: cheaper, faster, more practical, less resource-intensive, possible when population is very large or infinite.
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: s1 sampling
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: Extended Answer 6 marks: A town has 8000 adults: 3200 are aged 18–30, 2800 are aged 31–50, and 2000 are aged 51+. A researcher wants a stratified sample of 200 adults. (a) Calculate how many from each age group. (b) Describe how to select the people using simple random sampling within each group. (c) Explain one advantage of stratified sampling over simple random sampling for this survey about voting intentions. <div class="
(a) Total = 8000. 18–30: (3200/8000) × 200 = 80. 31–50: (2800/8000) × 200 = 70. 51+: (2000/8000) × 200 = 50. Check: 80 + 70 + 50 = 200 ✓ (b) Assign each person in the age group a number. Use a random number generator to select the required number of people. For 18–30, generate 80 unique random numbers from 1 to 3200. Repeat similarly for other groups. (c) Stratified sampling ensures each age group is represented proportionally. Simple random sampling might accidentally select very few from the 51+ group, meaning their views on voting are underrepresented. Since age affects voting intentions, proportional representation gives more reliable results. Mark scheme: M1 for correct proportions, A1 for 80, 70, 50, M1 for describing random number selection, A1 for clear method, M1 for identifying representation advantage, A1 for linking to voting context
Exam Tips: Always consider whether a sample is representative and free from bias | Know how to calculate numbers for stratified sampling | Understand the difference between the population and the sample | Be able to identify sources of bias in sampling methods | Remember: larger samples generally give more reliable results
Common Errors: Watch Out! 1. Wrong: Calculating stratified sample numbers that don't add up to the total sample size (due to rounding) Correct: Always check the sum matches the sample size — adjust the largest group if needed to account for rounding 2. Wrong: Confusing the population with the sample — e.g. saying "the sample of 1000 people shows 60% prefer tea, so exactly 60% of the whole country prefers tea" Correct: The sample gives an estimate — we can infer the population is likely around 60%, but it's not exact due to sampling error 3. Wrong: Choosing a "random" sample by asking your friends (convenience sampling) and calling it random Correct: Random sampling means every member has an equal chance —
AO3 - Reasoning & Interpretation: Reasoning and Interpretation A researcher surveys people about their income by standing outside a luxury car dealership on a Monday morning. 50 people are surveyed. (a) Is this a random sample? Explain. (b) What type of bias is likely in this sample? (c) How could the researcher improve the sampling method to get a more representative result? Answers: (a) No — people at a luxury car dealership are more likely to have higher incomes. Not everyone in the population has an equal chance of being selected. (b) Selection bias — the sample over-represents wealthy individuals and under-represents lower income groups. (c) Use stratified or simple random sampling from the general population, e.g. sele
Stretch & Challenge (Grade 8-9):
- Synoptic links: explain how s1 sampling connects to another Statistics topic you have studied
- Real-world: research one real-world use or example of s1 sampling
- Critical: "What are the limitations of the models used in s1 sampling?"
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 s1 sampling (10 mins)
- Exam practice: One past-paper question on s1 sampling from the board websites (15 mins)
- Extension: Explain s1 sampling to someone else in your own words (10 mins)