A question: how many times have we seen — or made — the mistake of calculating the average SERP position for a set of keywords and then using that number as if it were any other piece of data?
The average position is 4.3, keyword A is at 3 and keyword B at 7, “on average we are fourth”.
The problem is that a ranking position is not a number: it is ordinal data. The distance between position 1 and position 3 is not the same as between 3 and 5, and averaging numbers that do not have an interpretable distance — that is truly a meaningless operation.
Before performing any calculation on data, we must ask ourselves: what type of data is this? The answer determines everything we can — and cannot — do downstream. The answer comes from a classification that, although dating back to 1946, remains the foundation of every respectable statistical analysis: the 4 scales of measurement by Stanley Smith Stevens.
The scale of measurement does not serve to describe data: it serves to establish which operations are meaningful on that data. The more information a scale contains, the greater the number of statistical analyses we can apply. This is the criterion that makes Stevens’ classification so powerful and enduring in practice.
Continue reading “The Data: The 4 Scales of Measurement”