Secondary Data

What is secondary data?

• Data collected by the user for their current research question.

• Data collected by someone other than the user for a different purpose.

• Data that is always collected through surveys.

• Data that cannot be sourced from publications.

Which of the following is an example of secondary data?

• Personal interviews

• Census data

• Experimental results

• Direct observations

What is secondary research primarily concerned with?

• Analyzing existing data

• Conducting new experiments

• Developing new theories

• Creating new data

What is secondary research often referred to as?

• Field research

• Document analysis

• Experimental research

• Case study research

Why is secondary research also called 'desk research'?

• Because it involves fieldwork and direct observation.

• Because it requires laboratory experiments.

• Because you can collate the information from behind a desk, usually at a computer.

• Because it involves face-to-face interviews.

What is secondary research?

• A method of collecting primary data

• A method of analyzing primary data

• A method of using existing data instead of collecting new data

• A method of conducting experiments

Which of the following is NOT a use of secondary research?

• Re-analyzing existing data

• Re-using data to ask different questions

• Conducting new experiments

• Replicating to support the level of confidence

What is one of the benefits of increased access to substantial sample sizes in secondary research?

• It decreases the validity of findings.

• It supports increased validity and more generalisable findings.

• It makes research more expensive.

• It limits the scope of research.

What is a limitation related to secondary data?

• Relatively easy to analyse

• Data can be very consistent, precise and reliable

• Related secondary data is sometimes not available or accessing available data is difficult/impossible

• Findings can be generalised if selection process is well-designed and sample is representative of study population

Which of the following is considered a strength in data analysis?

• Difficult to understand context of a phenomenon

• Data may not be robust enough to explain complex issues

• Relatively easy to analyse

• Related secondary data is sometimes not available or accessing available data is difficult/impossible