What is the panel data of the econometer?

Data panel Econometrics is a specific form of statistical data analysis. It includes multidimensional data where data measures multiple things for the same subject. This naturally allows analysts to find more information and patterns, including cross reference data. The disadvantage of panel data is that it can be much more complicated to analyze. Most of the traditional economy includes the development of theories to explain and predict activities such as market behavior. Rather, the econometrics is about the beginning of the results and the attempt to work back to detect possible causes and connections. For example, a list of each child in the classroom would be common data. The list of each child in the classroom that gives the height of the child and the thmminess of the child would be a very simple form of prefabricated data. Some forms of prefabricated data are much more complicated: for example, the national census may contain dozens of data about every household.

It is possible to use relationships to establish relationshipst on the simplest prefabricated economist. For example, a set of data can show a test score for the university of former students and their salaries ten years after leaving school. This could show a strong relationship between a high score and a high salary. This does not necessarily prove that two are connected: a commonly used phrase is that "correlation is not equal to causal contexts."

More complicated panel econometrics can work with multiple factors. For example, test scores and salary data may also include details of the average test score at the Student School School. Analysts could find out that salaries are more important about how well the student compared to their classmates compared to their classmates than in the student's real score. This could lead to the theory that students overcoming peers are more competitive or controlled and that it is reflected in the fact that it will get in advance in the workplace and winning promotional actions.

Using multiple variables can make it easier to identify potentialh references. It can also reduce the chances that a particular connection was caused purely by chance, or it is clearer when it is. The main problem is that each additional variable causes a dramatic increase in the total number of explored potential references. This not only increases the desired analytical work, but also increases the chance that the error will slip.