Quick questions on Statistical sampling: methods, bias and the large data set - OCR A-Level Maths A

The right method depends on what is known about the population and what resources are available. If a sampling frame (a list of the population) exists, simple random or systematic sampling is straightforward. If the population splits into meaningful groups of different sizes, stratified sampling keeps each group represented.

Bias creeps in when some members are systematically more or less likely to be chosen. Common causes are an incomplete sampling frame (people omitted from the list), non-response (those who decline differ from those who answer), and self-selection (only the keen reply). Opportunity sampling at one place and time, as in the supermarket example, bakes in bias because it excludes everyone not there.

OCR provides a single pre-release large data set for the life of the qualification. You explore it during the course so you know its variables, units, structure and any missing values. Statistics questions may quote extracts or summary statistics from it and reward familiarity with real-data judgement, such as spotting that a variable has gaps or outliers.

A factory makes $5000$ items a day and wants a systematic sample of $100$. State the sampling interval. [1 mark]

Give one advantage of a census over a sample. [1 mark]