The correct answer is: D. degree of freedom
The number of observations in regression analysis is considered as the degree of freedom. This is because the number of observations determines the number of parameters that can be estimated in the model. For example, if there are 10 observations, then there are 9 degrees of freedom, because one degree of freedom is lost for the intercept term.
The degree of freedom is important because it affects the distribution of the test statistic. The smaller the degree of freedom, the more spread out the distribution of the test statistic will be. This means that a smaller p-value is required to reject the null hypothesis.
Here is a brief explanation of each option:
- A. degree of possibility: This is not a correct answer because the number of observations does not affect the possibility of a particular outcome.
- B. degree of average: This is not a correct answer because the number of observations does not affect the average of the data.
- C. degree of variance: This is not a correct answer because the number of observations does affect the variance of the data. However, the number of observations is not considered as the degree of variance.
- D. degree of freedom: This is the correct answer because the number of observations determines the number of parameters that can be estimated in the model.