Hlakanaphila Analytics

What it is

What do the terms, “qualitative analysis” and “quantitative analysis”, mean? Both involve the gathering of empirical evidence, that is, evidence based on observation, rather than on theory.

This evidence is also called “data”. Ways of gathering data include through surveys, interviews, focus groups, or by direct observation. Data on its own is of little use; it must be analysed in order to extract meaning. “Analysis” means the process of drawing inferences or conclusions, following certain logical or mathematical rules, from the evidence.

Where the evidence on which the conclusions are based is in the form of numbers (numerical data) then this process is called “quantitative analysis”; when the evidence is non-numerical (data in whatever form) it is called “qualitative analysis”.

We use the term “quantitative analysis” rather than the narrower term “statistics”, as the latter is often confused with the data itself.

Some Problems

Everyone is familiar with the tired aphorism “Lies, damn lies, and statistics”; yet data cannot lie; it can only be wrongly analysed. In truth, as Gary King of York University has pointed out, it is actually far harder to lie with statistical data (and get away with it) than without it.

Errors in analysis can take a number of forms:

Asking too Much

Analysis often attempts too much. Properly applying the rules of quantitative analysis usually means that the conclusions that can be drawn from a particular data set are limited in scope. Unfortunately, it is often hoped that data will provide all kinds of answers. Very often, it is simply not possible to design an affordable empirical study that will answer all the questions that need to be answered. Empirical studies have to be designed with a very clear, precise and circumscribed research question in mind if analysis is to be correct and not misleading.

Thoughtless Number Crunching

In this era where software programmes can effortlessly carry out “number-crunching”, there is a danger that analysts might lose sight of what the particular equation being applied should be employed for, and whether it is appropriate to use in that particular circumstance. Sometimes calculations are carried out in a routine manner, even though it is not appropriate for the research question being addressed.

Starting With the Answer

Another problem is that those commissioning research often do so with a particular outcome in mind. Their vested interest in that outcome places pressure, whether wittingly or unwittingly, on the analyst to answer the research question in a particular way. The client is short-changed where an analyst succumbs to pressure – only a truthful analysis can possibly serve a client’s interests.

Scary Mathematics

Because quantitative analysis involves complex-looking mathematical equations, calculations and statistical vocabulary difficult for the ordinary person to interrogate, most people have no way of knowing whether an analysis is in any way accurate; they end up having to go on a gut feeling about whether the conclusion drawn “sounds right”. The media also often presents results incorrectly due to a lack of understanding.