# What falls under data analysis

## Data analysis

*statistical data analysis;* Statistical methods with which summarized information (parameters) can be obtained from available individual data and documented in tabular or graphical form.

1. *Descriptive data analysis:* If there is a total survey or a data set in general, it is the task of the data analysis to condense the information contained in the individual data and to present it in such a way that the essentials become clear. Tables, graphical representations and characteristic dimensions are used for this purpose. The data analysis has an exclusively descriptive character (descriptive statistics).

2. *Inferential data analysis:* In a sample survey (partial survey), the focus of the data analysis is on transferring the sample findings to the population on the basis of a statistical model. Essential methods of inferential statistics are point estimation, interval estimation and hypothesis testing (statistical test methods). In this case, data analysis includes, for example, specifying point estimates or specifying confidence intervals for parameters of the population.

3. In addition to the descriptive and inferential, the *exploratory* and the *confirmatory* Differentiated data analysis. In exploratory data analysis, the available data volume is processed with the intention of revealing structures in the data or simple or manageable relationships or to discover them in this way. In contrast, the aim of confirmatory data analysis is to check relationships (e.g. regression analysis or the LISREL approach (LISREL) of causal analysis).

4. When analyzing data, there is a general between *univariate, bivariate and multivariate *To distinguish between data analysis, depending on whether a (one-dimensional) feature or two- or multi-dimensional features are in the foreground (univariate analysis methods, bivariate analysis methods, multivariate analysis methods).

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