Free Essay On Statistics

The meaning of the word “correlation” is "relationship." If a change in one variable is accompanied by a change in the other variable, then we can talk about the correlation between these variables. The presence of correlation between two variables does not say anything about the causal relationship between them, but it gives us the opportunity to develop a hypothesis about causation. The absence of the correlation indicates that we have to reject the hypothesis about the causation between the variables. A separate methodological problem is the so-called "false correlation". This is a correlation (sometimes, it is even a quite strong relationship) between variables, which obviously cannot be mutually dependent on each other. The reason is the presence of certain common factor omitted in the analysis, that affects each of the variables examined. For example, the correlation between the types of lipstick and the political beliefs of women may be explained by their social position and wealth. False correlations as well as the factors that cause them can be identified only by thorough theoretical analysis of the relationship between the variables. In order to eliminate false correlation, researchers often use partial coefficients of correlation.
Consider an example: there is a strong positive correlation between shoe size and the ability to pass intelligence tests. If you undertake such a study, we find that people with large size shoes are better in intelligence tests. The reason for such conclusions in the presence of the relationship of these two factors, the third factor - age. As a rule, children wear small size shoes. Over the age, the stop is growing and adult footwear is larger. It is clear that the average adults cope better with the intellectual tasks than children.