Feb 15, 2011
The Concept Degrees of Freedom
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The term number of degrees of freedom (degrees of freedom) is defined as the total number of observations in the sample (= N) minus the number of control (linear) free or limitation (restriction) is placed on earlier observations. In other words, the number degrees of freedom is the number of free observations of a total of observations N. So the general formula for determining the degrees of freedom (db) is the total observations (N) minus the number of parameters that are estimated or df = N - number of parameters estimated (k). (Gujarati, 1978).
Based on such understanding, it can be understood that the formula will be different degrees of freedom for the case of one observation with another observation case, and that makes the difference is depending on the number of estimated parameters. Therefore the formula of degrees of freedom can db = N - 2 or db = N -3 depending on the number of parameter (variable) had a crush. For example, if we want to examine two variables, the degree kebebasanya is db = N - 2. Why N - 2, because there are two variables.
Another thing that needs to be understood in the study of degrees of freedom is related to the research sample. The basic idea is every time we estimate the parameters (characteristics of the population), we will lose one degree of freedom. Therefore, degrees of freedom as told Gujarati (1978) will always N - k, not N. To understand this consider the following explanation: Suppose there is a population with an average (mean) is 10. Next we allowed to take a sample of 10 people from the population. The question is how many people we can take for free? For example, we take the first person freely, he has a score of 14. The second man is still free, he has a score of 8. Then the third consecutive person to person-to-nine were taken independently by score: 15, 6, 11, 14, 8, 6, and 5. What about the tenth? Was taken freely? Of course the answer is no. Ten people can not be taken freely again. If you already have 9 digits, numbers to ten no longer be determined freely in order to get the same estimate (ie mean = 10). For example, the number of scores from the nine people earlier were 87. In order that we get the same estimate, ie mean = 10, the tenth shall be determined by 13. Thus we can say we lost one degree of freedom. Well degrees of freedom is then used to see the value of a particular table, such as table t.
In our earlier calculations, we estimate only one parameter or estimate. Therefore, we only lost one degree of freedom, so the degrees of freedom that we have is N - 1, ie 10-1 = 9.
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