### Help with the interpretation of a statistic

In many disciplines and areas of research, statistics are used to substantiate theses and are therefore indispensable in science. Because statistics provide credibility and reliability, they are also used and presented on television, in newspaper articles or online. However, reading and interpreting a statistic correctly requires learning so that one can assess the actual value for each question. In general, one can say that not every statistic is meaningful.

A statistic should represent a scientifically relevant fact numerically and thus help the researcher. It will be used very different forms. A statistic can, for example, be displayed in tabular form, as a column or pie chart or as a graphic. In science, every statistic is explained by an attached text.

Our help in interpreting statistics first focuses on the correct reading of scientific statistics. It begins to capture the theme, all content and the design of the statistics. Different types of statistics also show different values, we help you to assess them correctly. Then the core data has to be analyzed, such as the sample, the period, the values contained (absolute values or percentages?) And what information the statistics should make. Help can also help to identify the key messages and identify the individual aspects they contain.

It is also often necessary to divide between relevant and unimportant data and consider the choice of data, the period of data collection, the measuring instrument and ultimately the significance of the results. If one analyzes these data correctly, statements on the quality of the statistics can be made. Our help also lets you detect missing data or errors in the evaluation and design of the statistics. For example, one should also look at the authors and clients in the critical consideration of a statistic.

Our help in evaluating statistics is also to support a realistic and critical assessment. Often, statistics are influenced by the research intent or subjective intentions of the researchers. Therefore, we strive to maintain a critical-distanced perspective at all times in order to evaluate a statistic, so that the evaluation can finally be done correctly.