Types of data

Explain Quantitative Data

are numerical data that typically represents how much, how long or how

many. Quantitative data collection techniques usually gather numerical data in the form of

individual scores from participants such as the number of words a person is able to recall in

a memory experiment. Experimental methods, and self-report methods using closed

questions typically gather quantitative data.

Explain Qualitative Data

are non-numerical data that describes the characteristics of something and

is typically in the form of descriptions, words, meanings, pictures and texts. Qualitative data

collection techniques can include transcripts from interviews, diary extracts, or written

accounts of what a researcher saw in an unstructured observation. Self-report methods such

as unstructured interviews and open-ended questions gather qualitative data.

Explain the differences between Quantitative and Qualitative Data

What is the strength of Quantitative data?

Quantitative data tends to be more objective than qualitative data, which means it can be

easily analysed using descriptive and inferential statistics. This means comparisons and

conclusions can be drawn easily.

What is the limitation of Quantitative Data?

A limitation of quantitative data is that due to it lacking detail this may decrease the

validity of the findings, for example whilst using a questionnaire with closed questions,

participants may be forced to choose an option that does not quite fit which could

invalidate the data.

What is the strength of Qualitative Data?

Qualitative data provides rich and detailed information which means researchers gain

meaningful insights into the motivation of participants giving it high ecological validity.

What is the limitation of Qualitative Data?

Analysis of qualitative data relies on subjective interpretation by the researcher which

could be inaccurate due to investigator bias.

Explain Primary Data

are data that is gathered directly, first-hand from the participants themselves

and are collected specifically for the purpose of the study by the researcher. The data are

specific to the aim of the study and have not been published before. For example, data

collected from an interview.

Explain Secondary Data

are data that have been previously collected by a third party, someone

other than the person who is conducting the research; are not specifically for the purpose of

the study but are used by the researcher. It can be data that have been collected for another

piece of research, which has been published before or data that already exist before the

research has begun. For example, data from journal articles or government statistics

Explain the differences between primary and secondary data

What is a strength of primary data?

A strength of primary data is that there is less chance of researcher bias because the

researcher has collected the data themselves. Therefore, they know the data is unchanged

and has not been manipulated by another researcher

What is a limitation of primary data?

A limitation of primary data is that it is a very lengthy and therefore expensive process. Simply

designing a study takes a lot of time due to recruiting participants, conducting the study and

analysing the data.

What is a strength of secondary data?

A strength of secondary data is that it reduces the amount of work that the researcher has to

do on a topic as the data has already been collected, therefore it is quicker to obtain the data

than if you were to design and carry out the study yourself.

What is a limitation of secondary data?

A limitation of secondary data is that it is impossible to know everything about the secondary

source as there is always the chance that the original authors left something out or

interpreted the data incorrectly leading to bias.

Explain Meta-analysis

A meta-analysis is a statistical technique for combining and analysing the findings of several

studies, which focus on the same research question and methods of research. The combined

data is often statistically tested to provide an overall conclusion. Meta-analyses use

secondary data.

What is a strength of a meta-analysis?

Analysing the results from a group of studies rather than from just one study can allow more

reliable conclusions to be drawn.

What is a weakness of meta-analysis?

The research designs in the different studies sampled may vary considerably which means

the studies are not truly comparable, this means the conclusions from a meta-analysis are

not always valid.