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The term "Logistic regression" is referring to the graph of analysis in predictions. There are variables involved and explain probabilities that are a hypothesis of the dependent variable, which is the one being applied to a future prediction.
Ah, the stochastic error term and the residual are like happy little clouds in our painting. The stochastic error term represents the random variability in our data that we can't explain, while the residual is the difference between the observed value and the predicted value by our model. Both are important in understanding and improving our models, just like adding details to our beautiful landscape.
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There is no such term. The regression (or correlation) coefficient changes as the sample size increases - towards its "true" value. There is no measure of association that is independent of sample size.
LCM is an abbreviation for "least common multiple."