Analysing the Mandela Effect

We have enough metrics to be able to perform some basic Mandela Effect analysis. This is gathered from various sources including Google Analytics for the site itself and breakdowns of the data classifications based on date and category.

There's no way these can be definitive - for a start we're looking at stats for a false memory phenomenon which itself is disputed to even exist. Other sources and attempts to find patterns have been made too, for example Google Trends. This, however, is the take on it based on this site. So when we show the sex of those "affected" by an alternative memory, we're really showing that of visitors here, which is almost certainly a different thing but of enough interest to be better than nothing.

Category

Each of the calalogued Mandela Effects has been filed into a category. Here are the figures for that category distribution, the most popular being "people" and the least being a tie for "geography" and "religion":

HE Categories 2017 09 Sep

Year

Here we see the values for the year the Mandela Effect applied to. This required considerable value judgement - it is based on the year component of the classification itself, as in "HE-{year}-nnnn". The block size represents a 5 year span, so it shows the second world war is tying with the early 80's for first place. Only dates from 1900 onwards were considered.

HE Year 2017 09 Sep

Sex

Based on Google Analytics site visitors, a roughly 50/50 split is what you'd expect:

HE Sex 2017 09 Sep

Age group

Peaking for the 25-34 year old age group, the stats for age show a marked decline from then on to virtually nothing for the 65+ group. This is based on site visits and probably the least representative, since it is also the distribution of internet users as a whole.

HE Age 2017 09 Sep

These values represent the total since the site records began.