Lesson 12: Types of Data

Question 1

Quantitative data

Answer 1

Data that involves numbers and can be measured objectively.
Includes:
- dependent variable in an experiment
- closed questions in questionnaires
- structured interviews
- a tally of how many times a behavioural category is seen in an observation

Question 2

Qualitative data

Answer 2

Data that involves words and the data is based on the subjective interpretation of language. It is only quantifiable if the data is put into categories and the frequency is counted.
Includes:
- open questions in questionnaires
- a transcript from an unstructured interview
- researchers describing what they see in an observation

Question 3

Difficulty of qualitative data

Answer 3

It is challenging to analyse because it relies on interpretation by the researcher, which could be inaccurate, subjective or even biased. Furthermore, qualitative data may not be easy to categorise/collate into a sensible number of answer types. The researcher could be left with lots of individual responses that cannot be summarised.

Question 4

Primary data

Answer 4

Is collected directly by the researcher for the purpose of the investigation.

Question 5

Secondary data

Answer 5

Information that was collected for a purpose other than its current use. The researcher could use data collected by them but for a different study, or collected by a different researcher. They may make use of government statistics, such as mental health statistics collected by the NHS. When the desired research already exists there is no need to conduct more research. However, there is substantial variation in the quality and accuracy of secondary data and it can be hard for researchers to know how reliable secondary data is.

Question 6

Meta-Analysis

Answer 6

Refers to the process of combining results from a number of studies on a particular topic (secondary data) to provide an overall view. Meta analysis- allows us to view data with much more confidence and results can be generalised across much larger populations. However, they may be prone to publication bias; the researcher may choose to leave out studies with negative or non significant results.