Abstract:

It is very difficult for students of economics to distinguish between basic and sample characteristics in statistics. Why is it not necessary to perform point and interval estimates when working with a base set (population), while when working in a sample set, we normally do this? Why is it necessary to test hypotheses, for example, about the mean value - after all, the average somehow worked out for me, is it a specific number and why should I test this number? And how is it that the arithmetic mean is a random variable? After all, it's a specific number that I calculated from the data. Similar types of questions are commonly encountered when teaching the basics of statistics to students of economics. The authors of this article have many years of experience in teaching statistics and try to answer the above questions (and many more) to students so that they understand the essence of statistics. Thus, the article does not contain a discussion of specific statistical procedures, but tries to approach the very philosophy associated with the teaching of statistics with a certain distance and insight. The authors try to develop in students a quantitative way of thinking and understanding the quantitative quantities that they encounter in economics as well as in everyday life. It turns out that far more important than the ability to calculate something is the ability to understand why some things count and how we should understand the results. It is therefore a general concept of teaching statistics in such a way that we focus less on results and methods and are more concerned with the overall context and philosophy of statistics.

Keywords:

Teaching statistics, population, random sample, hypothesis testing, philosophy of statistics.