Statistics

To evaluate the global economic situation in the 21st century, one must look at several factors. We went through a difficult period at the beginning of the 21st century. A global financial crisis occurred, and this crisis affected many countries. However, after the crisis, the world economy recovered, and many countries recorded economic growth. Nevertheless, since growth is not always distributed equally for everyone, some countries or segments of society benefited more than others. 

Therefore, for example, we can say that income inequality is a significant factor in economic deterioration. In some countries and regions, income inequality has increased, and with the weakening of the middle class, economic difficulties have begun to become apparent. We can see these by examining factors that must be considered in evaluating the economic situation of a country or region, such as unemployment rates, inflation, debt burden, and other economic indicators.

Furthermore, when evaluating global economic conditions, environmental factors must also be taken into account. As I emphasized in my previous article, factors such as climate change, the depletion of natural resources, and environmental degradation can affect economic conditions in the future. Therefore, all these factors must be continuously monitored and measured, and necessary corrective decisions must be taken by looking at deviations, and efforts must be carried out in this direction. This is where statistics comes into play. 

As a discipline, statistics has largely developed over the last century. Before that, probability theory, which is the mathematical foundation for statistics, was developed between the 17th and 19th centuries based on the works of Thomas Bayes, Pierre-Simon Laplace, and Carl Gauss. Unlike the purely theoretical nature of probability, statistics is an applied science concerned with the analysis and modeling of data. The roots of modern statistics towards the end of the 19th century are based on the works of Francis Galton and Karl Pearson. Ronald Aylmer Fisher also became one of the pioneers of modern statistics in the early 20th century, putting forward the fundamental ideas of “experimental design” and “maximum likelihood” estimation. 

However, it is John Tukey who made statistics what it is today, as it is widely used. In his highly influential article titled The Future of Statistics, published in 1962, John Tukey suggested a different approach, stating that the field of statistics was not progressing and that there was too much focus on “mathematical statistics” and not enough focus on the analysis of data. In a move against the prevailing philosophical doctrines in statistics, Tukey took the first step in the statistical revolution by proving himself not as a statistician, but as a “data analyst.” However, it was not until the publication of his masterpiece Exploratory Data Analysis in 1977 that Tukey moved the discipline of statistics away from the difficulties of statistical inference into a new field known as “Exploratory Data Analysis” (EDA). Tukey viewed EDA as a form of “numerical detective work.” 

So, what kind of result does this approach yield? What use can it be to us? First and foremost, EDA is the most appropriate approach to analyze the astronomically increasing amount of data of our day, which we define as big data. Thus, instead of getting lost in piles of data, it becomes possible to reveal the “patterns” contained in this data by taking measurements and to predict long-term developments, which we call trends, and to foresee our global economic situation. 

The greatest uncertainty for humanity is what will happen in the future. We think about this not for ourselves, but for our children. Exploratory analysis of past data gives us the opportunity to lift this veil of uncertainty, at least to some extent, and to predict the future with a certain margin of error. Of course, for those who understand statistics. In other words, just like car headlights, it allows us to “see what lies ahead” in the dark. Therefore, let us not be afraid of statistics. Acting on the saying “the past is our friend,” let us look at past data and work to make our future a more livable place with better conditions.