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Statistics and probability
Lesson 71 of 75
Introduction

Collect and classify data

Objective. Distinguish data types and design sensible collection methods.

  1. 1. Learn
  2. 2. Worked example
  3. 3. Practice
  4. 4. Feedback
  5. 5. Continue

Learn: the key idea

Data collection involves gathering information systematically, often through surveys, experiments or observation, so it can be analysed and interpreted afterwards. A good data collection sheet or tally chart has clear, non-overlapping categories that cover every possible response, allowing each piece of data to be recorded exactly once. Questions used to collect data should be clear, unbiased and offer appropriate response options, avoiding leading language that might influence the answer given. Choosing an appropriate sample size and method also affects how reliable the collected data will be for drawing conclusions.

Worked example

A survey question asks, 'Don't you agree that football is the best sport?' Explain the issue with this data collection question and suggest an improvement.

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Illustrated card showing ?
  1. 1Identify the wording used: 'Don't you agree' suggests a particular answer is expected.
  2. 2Recognise this as a leading question, which biases the data collected.
  3. 3Consider what a neutral version would ask instead.
  4. 4Suggest rewording to remove the bias.

Answer: The question is leading; it should instead ask neutrally, 'Which sport do you think is the best?'

Concept mastery

Based on your past attempts at this lesson — the question types to practise again come first.

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Practice

Practice happens on its own screen, one question at a time. Answers stay hidden until you submit yours, and you can stop and pick up at the same question later.

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Common mistake. Pupils sometimes design data collection categories that overlap, such as age ranges 10–20 and 20–30, making it unclear where 20 belongs. Always ensure categories are distinct with no overlapping boundaries.

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