Collecting Data - Gathering and Organising Information
Before we can analyse data, we need to collect it. Collecting data means gathering information in an organised, reliable way so that it can be counted, compared, and interpreted. Every survey, experiment, and census begins here.
One of the oldest large-scale data collection efforts in history is the census: ancient Egypt, Babylon, and China all conducted population counts thousands of years ago, mainly to work out taxation and military conscription, and the Domesday Book compiled in England in 1086 recorded landholdings across the country in extraordinary detail. Modern data collection became a proper science in the 20th century thanks to statisticians like Ronald Fisher, who developed rigorous methods for designing fair experiments and surveys so that the data collected would actually support reliable conclusions rather than misleading ones. Good data collection still matters enormously today: political polling companies, medical researchers running drug trials, and tech companies analysing app usage all live or die by whether their raw data was gathered carefully and without bias in the first place.
Types of Data
Qualitative data describes qualities or categories – colour, favourite subject, type of pet.
Quantitative data describes quantities or numbers – height, age, test score.
Quantitative data is further divided:
Discrete data takes only whole-number values (number of students, goals scored).
Continuous data can take any value in a range (height, weight, time).
Methods of Collecting Data
| Method | Description | Example |
|---|---|---|
| Survey / Questionnaire | Written questions answered by people | Favourite colour poll in class |
| Observation | Watching and recording events directly | Counting cars passing a junction |
| Experiment | Testing under controlled conditions | Recording times of a bouncing ball |
| Existing records | Using data already gathered | School attendance registers |
| Interview | Asking questions face to face | Customer satisfaction interview |
Tally Charts
A tally chart is one of the simplest ways to record data as you collect it. Draw a vertical stroke for each item; every fifth stroke crosses the previous four diagonally, making groups of five easy to count.
| Colour | Tally | Frequency |
|---|---|---|
| Red | ‖‖‖ (III) | 3 |
| Blue | ‖‖‖‖ ‖ (IIII I) | 6 |
| Green | ‖‖ (II) | 2 |
| Yellow | ‖‖‖‖ (IIII) | 4 |
Frequency Tables
A frequency table records how often each value or category appears. Once collected, raw data is organised into a frequency table before being displayed as a chart.
Worked Examples
| Method | Frequency |
|---|---|
| Walk | 12 |
| Bus | 10 |
| Car | 6 |
| Cycle | 2 |
| Total | 30 |
Key Takeaways
- Data can be qualitative (categories) or quantitative (numbers).
- Quantitative data is discrete (whole numbers) or continuous (any value).
- Tally charts record data as it is collected; frequency tables summarise it.
- Always check that the total frequency matches the number of items collected.