One way to think of degrees of freedom is how many datapoints can move independently (as in, be anything you want) while maintaining the same average. So, think of a dataset of two numbers. If you move one of the two numbers in that dataset, the other one HAS to change in order to maintain the average of the pair. Thus, this dataset would only have 1 degree of freedom as only one datapoint can move freely while the other must move in-tandem with the other.
In statistics, degrees of freedom is best understood as a way to numerically quantify the sample size in conjunction with the number of treatment groups. Bigger sample sizes increase degrees of freedom, more treatment groups reduce degrees of freedom.
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