Understand populations and samples, use random and other sampling methods and recognise bias, design data collection including questionnaires, and classify data as qualitative or quantitative and discrete or continuous.

What this dot point is asking

This is the data-handling foundation of WJEC statistics. You are asked to understand the difference between a population and a sample, to choose a sample using random and other methods while avoiding bias, to design data collection (especially questionnaires), and to classify data correctly. Statistics begins with how data is gathered, because a poorly chosen sample or a leading question makes every later calculation worthless. The exam rewards clear descriptions of sampling methods and sharp criticism of flawed survey questions, both worded-answer skills.

Populations and samples

Studying a whole population is often impractical, so we sample.

So to find the average height of students in a school of $900$, you might measure a sample of $60$ rather than all $900$, provided those $60$ fairly represent the whole school.

Sampling methods and bias

How the sample is chosen decides whether it is fair.

The exam often gives a flawed sampling plan (surveying shoppers on a weekday morning, say) and asks why it is biased. The answer names the group that is over- or under-represented.

Designing data collection

Questionnaires must collect data fairly and clearly.

A good survey question is clear (no ambiguity), neutral (not leading the respondent to an answer), and offers response options that do not overlap and cover all cases. For example, age groups "$0$ to $10$", "$10$ to $20$" overlap at $10$; better are "$0$ to $9$", "$10$ to $19$". A data collection sheet or tally chart records responses efficiently. Recognising and fixing a leading or loaded question is a recurring two-mark task.

Classifying data

Data falls into types that decide which charts and averages suit it.

Why this matters

Sampling and data is the entry point to the whole statistics strand and is examined as worded reasoning rather than calculation, so it tests AO2 and AO3 directly. The skills (choosing a fair sample, spotting bias, criticising and improving survey questions, classifying data) appear in short, reliable mark-earning questions, and the data type determines whether you later use a bar chart or a histogram, a discrete or a grouped frequency table. Getting the foundation right makes the calculation topics that follow meaningful.