The data sets determine the degrees of freedom for the F-test, nit the other way around!
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The Coefficient of Variation is a ratio showing the degree to which individual points of data in a sample deviate from the mean. It is calculated by taking the standard deviation of the sample and dividing that by the mean of the sample. It can be useful for comparing different data sets because it is a ratio (or percentage) and not an absolute number.
To simplify analyses for large data sets. To simplify analyses for large data sets. To simplify analyses for large data sets. To simplify analyses for large data sets.
They are groups of data.
A basic summary of data or a simple comparison of a few sets of data.A basic summary of data or a simple comparison of a few sets of data.A basic summary of data or a simple comparison of a few sets of data.A basic summary of data or a simple comparison of a few sets of data.
In fitting a logistic regression, as in applying any statistic method, the required sample size depends on the level of dispersion in the population and the quality of the statistics that you are prepared to accept. Usually there will be some information available somewhere (in the literature, say, or from colleagues) suggesting what level of variability to expect in data that is collected. This can be used to simulate some data sets and the logistic regression results that would arise from them. By varying the sizes of the data sets you can make a judgement. Once you have collected your first sample and fit the actual logistic regression to it you will have a much better idea how much data is actually required for useful estimates.