The morning begins with analyzing statistics: “What happened yesterday? Are there any complications? Does everything work?” A quick glance at the distribution graphs — everything is in order, no deviations, everything works like clockwork. You can do your current business. We start sorting through your mail:
most people use statistical data to solve applied problems, in our case, this is analyzing website traffic, analyzing the progress of an advertising campaign, analyzing consumer behavior. In this situation, you need to be able to quickly evaluate statistical calculations so as poland whatsapp data to spend a lot of time on daily analysis, but at the same time always be aware of events. Here, as in the course of mathematical analysis, knowledge of standard distribution graphs will come to the rescue.
Standard distribution graphs show audience trends that change slightly over time. For example, we know that about half of the site's audience is in Moscow and its region, therefore, the site's hourly traffic graph will mainly obey Moscow time. Similar standard graphs can be built for almost all audience parameters that do not depend on the site's advertising activity.
Knowing the standard audience distribution graphs allows you to quickly assess the state of affairs on the site, since any significant deviation from these graphs implies some event. Knowing the standard graphs allows you to get the overall picture in a matter of seconds, and to develop them further only in the event of serious deviations. Deviations themselves are a very interesting topic and in the Global Statistics project we have a whole section on interesting trends. Below are the most important standard graphs with short explanations for each of them.
All standard graphs are determined by general social trends and those general audience parameters that do not change or change little over time; deviation from them is a sign of unnaturalness. For example, it is obvious that people prefer to work during the day, have fun in one way or another in the evening, and sleep at night. All this is reflected in the statistical graphs and can be very easily traced even with a superficial study.
This series of articles reflects those standard distribution graphs that are most often required for everyday work. The change in these graphs over time is extremely insignificant or equal to zero, however, we constantly monitor the Network, including for changes in standard graphs, so in the event of a noticeable change, the data in the article will be immediately updated.