The various distributions in the reading this week and last week entail probability curves that mathematically differ according to a group of parameters. Different parameters allow for the specification of the shape, scale, and location of the distribution.

Discuss the role that these parameters play in establishing the characteristic form for each distribution. Consider why our text doesn't discuss the location parameter very much. Why might that be? Also, if we strip away these parameters from the various distribution formulas, what's typically left? Treat this thread as a conceptual exploration, not a detailed mathematical proof.

example discussion:

The various ditributions that we been looking are highly dependant on the parameters that we choose. For example at the beginning of the semester we were talking about normal distributions and its various behaviors like skewness and kurtosis, this calculations are a result of the data that we choose to study, we use this behavior to further analyse our distributions. I think that the reason why the textbook does not center much around the exact location of the parameter is because we want to see the entire picture, we analyze the entire graph rather than a speific spot on it. I would guess that if we strip away these parameters away from the formulas we use, we are not going to end up with a good estimation of the probability, for example if we are doing binomial distribution we wouldn't end up with an accurate probability of success.