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Often times there are so many variables involved in a study that it is difficult to distinguish causes. For example, there is the belief that
Often times there are so many variables involved in a study that it is difficult to distinguish "causes". For example, there is the belief that "smoking causes lung cancer". I tend to believe this myself but my own mother was a chain smoker and never developed lung cancer. There are many other variables that might affect the outcome of lung cancer such as working conditions, heredity, diet, etc. It is too hard to account for every "factor" in these circumstances so we might just focus on one such as studying lung cancer patients and asking them if they smoked or not. In this discussion, you are going to come up with some example of the binomial probability distribution. Remember our definition: Def: Binomial probability distribution 1. procedure has fixed # of trials 2. trials must be independent 3. each trial must have all outcomes classified into 2 categories 4. probabilities must remain constant for each trial
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