Quantitative vs qualitative data: methods, differences and examples

How to analyse qualitative and quantitative data

When it comes to the analysis of data, the methods unsurprisingly alter for each data approach.

Quantitative data analysis

As we’re dealing with numbers, statistical analysis is often applied to establish data patterns, with outcomes plotted in graphs or tables.

Generally speaking, you could be looking to discover things such as average scores, reliability of results and how many times a certain answer was provided.

Preparation of the data before it is analysed is incredibly important. The data gathered needs to be validated, any known errors removed, and remaining data coded. This process ensures the best quality data is going to be analysed and provides a more accurate and helpful outcome.

The two most used quantitative data methods for analysis are inferential statistics and descriptive statistics.

• Inferential statistics: show relationships between multiple variables, which means predictions can be made. Correlation explains the relationship between two variables, whereas regression shows or predicts the relationship between two. Analysis of variance tests how much the two variables differ from each other.
• Descriptive statistics: provide absolute numbers, but don’t explain the reasoning or context behind them. Useful to apply when there is a limited amount of research available and mostly used for analysing single variables.

Qualitative data analysis

As we’re dealing with words, images or video content, qualitative data can be more challenging to analyse.

Examination of any recurring themes within the data is a helpful approach to take, as is exploring the frequency of use of phrases or words. The idea, like quantitative data analysis, is to discover patterns.

Methodologies which could be used include:

• Grounded theory: establishing new theories from the data
• Thematic analysis: identifying patterns in meaning to determine themes
• Content analysis: interpretation of meaning from body content
• Narrative analysis: discover how research participants construct story from their own personal experience

Best data collection tools & techniques

Now that we’ve looked at various approaches to gathering data, let’s look at some specific tools.

• Qualitative data tools & techniques

While we might find ourselves using focus groups or interviews as a technique to collect data, tools such as ‘sentence completion’ or ‘word association’ can provide a wealth of further data to explore. With sentence completion, an individual is given a part-sentence to complete, and the answers provided give us an insight into the views and ideas of that person. Word association performs a similar function, where the individual is asked to share what comes to mind when they read or hear particular words.

• Quantitative data tools

When it comes to drilling down into the digits, you might embrace statistical software options such as SPSS, JMP, Stata, SAS, R or MATLAB.

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