Fundamentals of Statistics contains material of various lectures and courses of H. Lohninger on statistics, data analysis and here for more.

What is Data Analysis


Data analysis is a combination of
statistics, visualization methods and know-how

Many of the methods for data analysis are based on multivariate statistics, which poses an additional problem to the beginner: multivariate statistics cannot be understood without a profound knowledge of simple statistics. Furthermore, several fields in science and engineering have developed their own nomenclature assigning different names to the same concepts. Thus one has to gather considerable knowledge and experience in order to perform the analysis of data efficiently.

Possible applications of statistical methods can be in the fields of

  • medicine
  • engineering
  • quality inspection
  • election polling
  • analytical chemistry
  • physics

Statistics and statistical methodology as the basis of data analysis are concerned with two basic types of problems:

(1) summarizing, describing, and exploring the data (descriptive statistics)
(2) using sampled data to infer the nature of the process which produced the data (inferential statistics)

Another important aspect of data analysis is the data, which can be of two different types: qualitative data, and quantitative data. Qualitative data does not contain quantitative information. Qualitative data can be classified into categories. In contrast, quantitative data represent an amount of something.

A third distinction can be made according to the number of variables involved in the data analysis. If only one variable is used, the statistical procedures are summarized as univariate statistics. More than one variable result in multivariate statistics. A special case of multivariate statistics with only two variables is sometimes called bivariate statistics.