← Unit 4 Data Collection and Sampling
MA5-DAT-C-01

Data Collection and Sampling

⏱ 25 min📚 Year 9📈
Think First

You want to know how students at your school feel about the cafeteria food. Should you ask only your friends?

💡 Revision: Ensure you understand basic statistical terms like population and sample.

Learning Intentions

Know

  • Population vs sample
  • Random sampling
  • Bias
  • Survey design

Understand

  • Why sampling is necessary
  • How bias affects results
  • When census is preferable

Can Do

  • Design an unbiased survey
  • Identify sources of bias
  • Choose appropriate sampling methods
PopulationSampleBiasCensusRandomStratified
Learn Phase
1

Population and Sample

Who are we studying?

The population is the entire group being studied.

A sample is a subset of the population used to make inferences.

Key Principle

A good sample is representative of the population.

A census collects data from every member of the population. This is expensive and time-consuming but gives exact results.

2

Sampling Methods

How to choose a sample

Common sampling methods:

  • Simple random: Every member has equal chance
  • Stratified: Population divided into groups (strata), sampled proportionally
  • Systematic: Select every $n$th member
  • Convenience: Choose readily available members (often biased!)

Random and stratified sampling generally produce the most representative samples.

3

Bias in Data Collection

What can go wrong?

Bias occurs when a sample does not represent the population.

Types of bias:

  • Selection bias: Sample not representative (e.g., only asking friends)
  • Response bias: Questions worded to influence answers
  • Non-response bias: Certain groups less likely to respond

Example: A phone survey during work hours underrepresents working people.

Check Understanding

Try it yourself

A school has 600 students: 300 Year 9, 200 Year 10, 100 Year 11. How many from each year should be in a stratified sample of 60?

Worked Example

Sampling Methods

1

A company has 1000 employees: 600 full-time, 300 part-time, 100 casual. In a stratified sample of 50, how many part-time?

Proportion: $300/1000 = 0.3$

Sample: $0.3 imes 50 = 15$ part-time employees

2

A survey asks: "Don't you agree that homework is excessive?" Identify the bias.

Response bias — the question is leading, suggesting homework is excessive.

3

A researcher stands outside a gym and asks people about exercise habits. Identify the bias.

Selection bias — gym-goers are not representative of the general population.

Common Misconceptions

A larger sample is always better. A large biased sample is worse than a small representative one. Quality matters more than quantity.

Random sampling means asking anyone you meet. No — true random sampling gives every member of the population an equal chance of selection.

Online polls are representative. No — they suffer from self-selection bias; only motivated people respond.

Your Turn

Practice — Sampling Practice

Work through each question in your book or digitally. Answers are in the Questions phase.

1Design a stratified sample for a school of 800 students across 4 year groups.
2A restaurant surveys only customers who pay by credit card. What bias is present?
3Explain why a census might be impractical for a national opinion poll.
Real-World Anchor

Market Research and Polling

Australian election polling uses stratified sampling to ensure representation across states, ages, and genders. The Australian Bureau of Statistics conducts the Census every five years, but conducts sample surveys (like the Labour Force Survey) monthly using carefully designed sampling methods.

📓 Copy Into Your Books

Population/Sample

  • Population = entire group
  • Sample = subset
  • Census = everyone

Methods

  • Random - equal chance
  • Stratified - proportional groups
  • Systematic - every nth
  • Convenience - often biased

Bias

  • Selection - unrepresentative sample
  • Response - leading questions
  • Non-response - some groups don't respond
Questions Phase
Check Your Understanding
Answer all questions correctly to unlock the Game phase.
A census surveys:
Stratified sampling divides by:
Asking only your friends is:
"Most people agree that..." in a question creates:
A representative sample:
Population 500, sample 50. Sampling fraction:
Online polls typically suffer from:
Systematic sampling selects:
1A town has 10,000 people: 4000 under 30, 5000 aged 30-60, 1000 over 60. Design a stratified sample of 200.
2A TV station asks viewers to call in and vote. Why might results be biased?
3Explain the difference between random and stratified sampling.

Comprehensive Answers

1Stratified sample of 200.
Under 30: 80, 30-60: 100, Over 60: 20.
2TV call-in vote bias.
Self-selection bias - only motivated viewers call in. Not representative.
3Random vs stratified.
Random: everyone equal chance. Stratified: population divided into groups, sampled proportionally for better representation.
MC 1Census surveys.
Entire population. Answer: B
MC 2Stratified divides by.
Proportional groups. Answer: B
MC 3Asking friends.
Convenience sampling. Answer: C
MC 4"Most people agree..."
Response bias. Answer: B
MC 5Representative sample.
Reflects population. Answer: B
MC 6Sampling fraction.
50/500 = 1/10. Answer: B
MC 7Online polls.
Self-selection bias. Answer: B
MC 8Systematic sampling.
Every nth member. Answer: B
SA 1Stratified sample.
80, 100, 20.
SA 2TV call-in bias.
Self-selection bias.
SA 3Random vs stratified.
Random gives equal chance; stratified ensures group representation.
Game Phase
🎲
Game Unlocked!
You have mastered the Check Your Understanding questions. Choose a game mode below.
📦
Classify & Sort
Sort mathematical objects by their properties.
Speed Challenge
Answer questions against the clock.
📈
Match Maker
Match problems to their solutions.