Experimental statistics

Experimental statistics are statistics that are in development, so that methods and sources may change in the process towards the final form of the statistics based on experiences, e.g. in the form of feedback from users.

In what ways do they differ from Statistics Denmark’s usual statistics?

In general, any statistics published by Statistics Denmark are official statistics. However, experimental statistics are not regarded as official statistics until they have been thoroughly tested to the point where they obtain a permanent form and a new status as official statistics.

It appears from the individual sets of statistics whether they have experimental status. The statistical documentation explains specifically what the experimental status of the individual set of statistics involves. It could be e.g. that the methods are not quite thoroughly tested, that new data sources are being tested, or that in its preliminary form, it only covers part of the intended area.

Which experimental statistics does Statistics Denmark publish?

Experimental statistics are gradually being developed to meet the demand of users. This page presents an overview of these, but in general, the individual sets of statistics can be found under the relevant subject pages or subjects in Statbank Denmark.

Is the uncertainty higher, and should you take special precautions when using it?

Limitations and reservations vary between the different sets of statistics and appear from the statistical documentation for each set of statistics.

Why does Statistics Denmark publish experimental statistics?

The purpose of experimental statistics is to respond to user requests for timely indicators of the development of society. Using more and more new sources and methods, we can create timely statistics in areas where the official and quality-checked statistics often have a time lag of months or perhaps years. Publishing the statistics in a preliminary form allows us to get feedback from the users, before we have found the final form, and thus gives us a more relevant product. At the same time, it gives the users an opportunity to become familiar with the statistics.

For instance, the experimental statistics could be a key indicator of a phenomenon that we describe through official statistics (e.g. Statistics Denmark developed a number of experimental statistics as indicators of the development of Covid-19). In other contexts, indicators can be official statistics, e.g. Consumer expectations.