Zähldaten

Zähldaten, also known as count data, are a type of statistical data that represent the number of times an event occurs within a specific interval or set. This interval can be in terms of time, space, or any other defined unit. For example, the number of customers entering a store in an hour is a count datum. Similarly, the number of defects found on a manufactured item or the number of bacteria colonies on a petri dish are also count data.

The key characteristic of count data is that they are non-negative integers, meaning they can only take values of 0, 1, 2, and so on. They cannot be negative or fractional. This discreteness distinguishes them from continuous data, which can take any value within a range.

Statistical analysis of count data often involves specialized distributions. The Poisson distribution is frequently used when events occur independently at a constant average rate. However, if the variance of the data is greater than the mean (a phenomenon called overdispersion), other distributions like the negative binomial distribution might be more appropriate. The analysis aims to understand the factors influencing the frequency of these events and to make predictions about future occurrences. Zähldaten are prevalent in fields such as public health (e.g., number of disease cases), ecology (e.g., species counts), marketing (e.g., website clicks), and quality control.