Data and its collection flashcards

Topic 1: Data and its collection

What is the difference between qualitative and quantitative data?

Qualitative data is described by categories, not numbers (for example eye colour). Quantitative data is numerical, and is either discrete or continuous.

What is discrete data?

Data that takes only certain, separate values: number of children, goals scored, shoe size. It is usually counted, but "counted vs measured" is a rule of thumb, not the deciding test.

What is continuous data?

Data that takes any value in a range: height, mass, time, limited only by the precision of the measuring instrument. It is usually measured, but that is a heuristic, not the definition.

Is shoe size discrete or continuous?

Discrete, even with half sizes. The deciding factor is that the possible values form a separate, listable set.

What is the difference between primary and secondary data?

Primary data is collected first-hand for this purpose, so you control what is measured and how. Secondary data already exists, collected by someone else for another purpose: quicker and cheaper, but no control over its accuracy or definitions.

When would you use a census rather than a sample?

When the population is small and complete accuracy matters. A sample is used when the population is large, or when testing destroys the item. A sample is cheaper and quicker but has sampling error.

Which four sampling methods does 0479 name?

Simple random, systematic, stratified and quota. A sampling frame is needed for all of them except quota.

How do you take a systematic sample, and what is its weakness?

Choose every nth member from a list, starting from a random start. It can be biased if the list has a pattern that matches the interval.

How do you work out the numbers for a stratified sample?

Number from a group = (group size ÷ population) × sample size. Round so the parts still total the sample size. Example: 300 girls and 200 boys, sample of 50 → 30 girls and 20 boys.

What is quota sampling, and what is its weakness?

The interviewer fills a set number of people in each category, choosing who to ask. It needs no sampling frame, but it is not random, so interviewer bias is possible.

Give sources of bias in a survey

An incomplete sampling frame, non-response, self-selection, leading questions, the interviewer effect, and response options that overlap or do not cover every answer.

Does taking a larger sample remove bias?

No. A larger sample reduces sampling error, but bias is a systematic error in the method, so a biased method stays biased at any sample size.