The following problem is an example of applying assumed distribution to addressing the prevalent business situation with uncertainty. it is an example of the more general technique of representing uncertainty as a random variable demonstrating that uncertainly doesn't mean you \"don't know anything\" or decisions are arbitrary or must resort to guessing or intuition. Frequently you will find your guesses or intuition will be far off from what is actually best! SuperMaxx Realty would like to advise their clients on their expectations on home selling sales for the area they are considering. a. Discuss on principles the degree it is ok or not ok to assume home sales prices would be Normally distributed. How might we validate this assumption if we were to use this in practice? Think about the characteristics of the Normal distribution compared to the characteristics of the home sales data. What characteristics matter most for this problem? Which do not matter? b. To use your assumption that the demand is Normally distributed, you will need to empirically estimate its two characteristic parameters, the mean and standard deviation. Use the PRICE data and the assumption that it is Normally distributed to estimate its mean and standard deviation. We want to estimate the population mean (mu) and population standard deviation (sig) from some sample data from a Normal distributed random variable. It may seem a little fussy, but you will want to compute the population mean and standard deviation from the data and not the sample mean and standard deviation. If using Excel, use =STDEV.P(PRICE). There's not