The power of the almighty statistic

Sophie Chalk explains how best to understand information and the way it is presented.

If you look hard enough (and you don’t always have to) there are statistics for everything. As a society, we love numbers and percentages. The internet is full of statistics for everything in our lives from the prevalence of health conditions to how much dust in the average home is made up of human skin (FYI – 70 per cent!). The national media often uses stats to create attentiongrabbing headlines and companies use them to spread awareness and sell products, presenting the numbers to support claims.

Sophie Chalk is an editorial managerat EK Communications.

A fact of life

that you wouldn’t typically think about. Did you watch the weather report this morning or check a weather app? Weather forecasting is the result of computer systems analysing historical and real-time data and using statistics to predict the future. Insurance companies do something very similar in order to calculate your risk of making a claim, hence why car insurance premiums go up after an accident, or why home contents insurance is higher for properties with fewer security features. Statistics are

used to predict government election results, prepare for upcoming natural disasters, guide financial investments and, in sports, for athletes to improve their performance. This kind of data also has a place in education with regards to marking and grade setting, as well as in the travel industry, where stats are utilised to dictate fluctuating flight prices or destination popularity based on demand.

In the dental and medical sectors, statistics are used by those in the industry and the profession. In practice, stats are used to observe and predict risk of disease, to help patients prevent health conditions and enhance their health and wellbeing. From a trade perspective, products and services are tailored to help dental professionals deliver the preventive care their patients need. Much more than that, though, statistics can be used to monitor changes in demand so that stock can be managed e ectively and business profitability optimised. So, statistics are good. They provide evidence from which we can improve our personal and work lives and can always be trusted… right? Not quite.

Check the source

A statistic is defined as ‘a fact or piece of data obtained from a study of a large quantity of numerical data’. But that doesn’t mean that what you see is always what you get. There are actually many di erent aspects to consider before a particular stat should be trusted and/or applied to your everyday life. While this is far more important in some areas than others, being aware of the numbers around you and what they really mean is important. In fact, there are many ways that a stat can be as misleading as it is useful. The definition above clearly states ‘large’ quantities of data are required for statistics, but what qualifies as ‘large’? This is often a big issue (and pet peeve for many) in consumer advertising. How many TV ads do you see every week presented by worldwide, household brands that promote a product based on “88 per cent of people would recommend our product to a friend” or something similar? Have you ever looked at the small print at the bottom of the screen? Some of these ‘statistics’ are based on the smallest sample sizes known to man – and if a multi-billion-dollar organisation with millions of customers cannot conduct surveys with more than a couple hundred people, then we should question how trustworthy the results really are. This brings us on nicely to the issue of relativity. Sample sizes must be relevant for what is being tested. Surveying 50 people for your average shampoo will provide a very poor representation of what people around the globe experience with the product. However, if you’re looking at something more niche, then a sample size of 50 might be more than adequate to reliably make a point. In medicine, for example, when studying rare diseases or syndromes, the sample size of any research may not be much bigger due to a lack of possible subjects. The sample size and how relevant a study is will also impact how e ectively a statistic can be applied in other situations. There is a plethora of research and scientific evidence in dentistry that manufacturers use to develop products and materials, and which clinicians utilise to deliver exceptional patient care. But it is essential that the right stats are being applied in appropriate circumstances. For instance, a study suggesting that a specific implant surface material provided 90 per cent survival rates for osteoporotic patients requiring a posterior restoration, does not necessarily mean that that surface material is best for all patients needing an implant anywhere in their mouth. We have to consider the specifics of the statistics and their relevance in di erent situations.

Reliability and jargon

Another factor that can influence the reliability of data and therefore of the stats created, is bias. If you deal with clinical products or have worked in R&D then you’ll be only too familiar with the potential for commercial bias when a study is designed and performed by an organisation in order to support benefits of its own product line. This is not always a bad thing – it’s still a great asset to be able to confidently state features of a product you sell and back them up with stats. It’s just important to remember that when comparing materials or solutions, to look out for anything in the surveys or studies that might swing the results in their favour.

Even once we have checked all of this, there is still plenty of jargon to interpret. Those in marketing roles will be familiar with the type of wording that companies are able to use when presenting results from a study, but others will need to look more carefully for it. What does it mean for an outcome to be ‘statistically significant’? The papers behind the numbers also tend to talk about ‘probability’, ‘aggregated means’, ‘analysis of variance’, ‘distribution’, ‘calibration sample’, ‘cointegration’, ‘double-blind’, ‘latent variable’, the list goes on. Then there’s the type of studies that produce the statistics – systematic reviews, meta-analyses, cohort studies… it’s truly a language of its own. Now, I’m not suggesting that we all have to learn these terms – it’s more about being aware of the wording used to better understand the relevance and importance of the statistics generated. For example, understanding whether the statistics came from a single case example or are an average of multiple cases will help determine how well they represent the population they relate to.

The foundations of the future

Despite all of this, statistics are still a prevalent and very important feature in the modern world. As societies go more and more digital, stats will be used to power a growing number of everyday technologies and have an increasing influence over our lives. When used correctly, this data can be utilised to more accurately evaluate trends, to predict future events and streamline our daily workflows. Statistics will remain a massive part of medicine and dentistry, helping clinicians to deliver the highest quality of preventive care while enabling manufacturers to create the solutions they need to do so successfully. Statistics can be a very powerful tool, but as we all know, with power comes responsibility. Being aware of the numbers you use to sell a product, as well as those used to sell to you, is important.