When you think of statistics, do you associate it with equations, mathematics and complex formulae? Have you also realised that there is a whole language associated with the area?

Learning and using statistics requires you to understand the language of statistics (Dunn et al. 2016). And let’s be honest, this language can sometimes be confusing as it borrows words from general English and mathematics. Often though, words have a very specific statistical meaning that may or may not correspond to their more popular meaning. This has been conned lexical ambiguity.

To make it even more difficult, the language of statistics is not even close to being standardised. Depending on the context or field of research, statistical terms can have acquired different definitions. This can make it particularly confusing for someone who is new to statistics or for an experienced researcher who starts working in a multidisciplinary team. These linguistic challenges can contribute to statistical anxiety, which we covered earlier this year.

For example, from Dunn et al., the word sample:

“In statistics, a sample is a set of observations drawn from a population. In business, however, a sample is a free small quantity of product and in biomedicine a sample is a single specimen (of blood, urine, etc.) rather than a set of observations.”

Similar to one word having different meanings, one concept can also be described by multiple words that are often used interchangeably. For example, linear mixed models are also known as mixed effects models, multi-level models, longitudinal models, etc. Each of these terms will be embedded in a particular field or software package. The challenge for those unfamiliar with the area is to recognise that these terms all refer to a similar model (note that there are slight nuances possible from a theoretical point of view).

Now, don’t be encouraged by these complexities. The key is to be informed and aware of lexical ambiguity. Just as with normal communication, when talking statistics, you will need to be conscious that the message that you are conveying is being interpreted as you intended by the receiver. Talking and understanding statistics will enable you to communicate clearer with your peers, supervisors and statistical consultants.

Next month we will look in a bit more detail at some of those lexical ambiguous terms. But for the time being, do not hesitate to ask clarification if you do not understand a term or are unsure about its exact meaning. Especially when you are communicating with the Statistical Consulting Unit. Our mission is to make you understand statistics better and we can only do that when we, consultants and researchers, are conscious of the meaning and understanding of our statistical language. And when something is not clear, clarification should be sought and encouraged.

References

Dunn, P.K., Carey, M.D., Richardson, A.M. and McDonald, C. (2016). Learning the language of statistics: challenges and teaching approaches. Statistical Education Research Journal 15, 8 – 27.