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or a pre-vector to be fully known). Degrees of freedom are also commonly used in related statistical testing problems, where the squared length, or 'square sum' of the coordinates, is related to the chi-squared parameters and other distributions.
As discussed above, the degree of the freedom is 378.

4.3 P Value
In frequency statistics, the p-value is relative to a statistical model, and its measurement observes how extremes are observed in the results of the sample's function (test statistic). They have abused controversial issues. The p-value is defined as the probability that the obtained result is equal to or greater than what is actually observed when the null hypothesis is true 'more extreme'. In frequency theory reasoning, p-values are widely used in statistical hypothesis testing, especially in the null hypothesis test of significance. In this method, for the part of the experimental design, a first choice of a model (null hypothesis) and a threshold for p is called the significance level of the experiment before performing the experiment, traditionally 5% or 1 %, And is expressed as α. If the p-value is less than or equal to the selected significance level (α), the test indicates that the observed data is not consistent with the null hypothesis, so the null hypothesis must be rejected. However, this does not justify the hypothesis tested. When the p-value is calculated correctly, the test guarantees a class error rate of at most [alpha]. A typical analysis using the standard α = 0.05 cutoff, when p <0.05, rather than reject when p> 0.05 null hypothesis was rejected. The p-value itself does not support hypothetical probabilistic reasoning, but only applies to tools that decide whether to reject the null hypothesis. The US Statistical Association, in its statement using the p-value, affirmed the usefulness of correctly interpreting the p-value, but cautioned that the p-value was generally misused and misinterpreted (Kreinovich&Servin, 2015). Using bright-line rules as truncation, such as for ≤ 0.05, no other supporting statistics The evidence, which is particularly criticized: commonly interpreted as 'P ≤ 0.05'. Although it is generally accepted that p values are often misused, there is no consensus on alternatives. 
As discussion above, the p-value is less than 0.001, so that the difference could be apparent. 
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