## 1/19 Quantitative data analysis

First of all let's define what we mean by quantitative data analysis.

It is a systematic approach to investigations during which numerical data is collected and/or the researcher transforms what is collected or observed into numerical data. It often describes a situation or event, answering the 'what' and 'how many' questions you may have about something. This is research which involves measuring or counting attributes (i.e. quantities).

What does this mean? Many of you will have seen adverts which say '8 out of 10 cats prefer Whispers cat food'. We're saying that in a survey of 10 cats, 8 of them preferred Whispers cat food. We've taken the cats, counted what they prefer and report the findings as numbers.

A quantitative approach is often concerned with finding evidence to either support or contradict an idea or hypothesis you might have. A hypothesis is where a predicted answer to a research question is proposed, for example, you might propose that if you give a student training in how to use a search engine it will improve their success in finding information on the Internet.

You could then go on to explain why a particular answer is expected - you put forward a *theory*.

Most often when a researcher is interested in hypothesis testing they will conduct an *experiment * to gather their data. So, we could take one sample of students, give them some training in how to search and then ask them to find some specific information. We ask another sample of students to search for the same specific information - and we see which group did better through a variety of different measures, some subjective and some objective.

More will be discussed on this later.

Bryman has written an interesting article about qualitative and quantitative research: **Integrating quantitative and qualitative research: how is it done? **

This is linked in the information box to the left.