Null Hypothesis

The initial (Null) hypothesis is one of the basic concepts in statistics and is the basis for conducting statistical tests. It consists of the assumption that there is no relationship between the variables that are studied in the study. This means that if we do not find any relationship between two variables, we can conclude that they have no relationship and therefore do not influence each other.

The null hypothesis can be formulated as follows: “There is no relationship between variable X and variable Y.” This means that we expect the values ​​of variable X to be independent of the values ​​of variable Y. If we find a statistically significant relationship between variables X and Y, then we can conclude that these variables do influence each other and have a relationship.

However, it is important to note that the null hypothesis is not an absolute statement, but only a guess. This means that it can be refuted if there is sufficient evidence. Therefore, it is important to conduct statistical tests and analyze the results to draw conclusions about the presence or absence of a relationship between variables.

In general, the null hypothesis is an important tool in statistical research and allows us to test the presence or absence of a relationship between variables without assuming its existence. However, its use requires caution and critical thinking to avoid drawing conclusions.

Initial hypothesis - a hypothesis that is considered at the first stage of testing and which can only be accepted in an alternative situation. Undoubted due to too small a sample or unknown experimental conditions; therefore, on the basis of this hypothesis, the true properties of any phenomenon are not tested.

One of the key points in scientific research is testing the hypotheses to make sure they are true, as well as highlighting contradictory parts of the study. To do this, a hypothesis testing procedure is used. It is first called "null hypothesis testing" and