Discuss why the mean and median of the distribution always approach each other as we take trimmed means at higher and higher percentages (e. g., 10%, 20%, 30% in particular, describe what is happening to the kurtosis and skewness of the distribution as we trim off more and more data. speculate on whether or not you might expect to see an optimum point in that process at some value between the mean and median. why might this matter?

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step-by-step explanati∵∵∴∴on:

if the probability is 1/12, 75 people will receive a $25 gift card

step-by-step explanation:

take the logarithm of both sides (the base of the log doesn't matter):

apply the exponent property - this says that :

distribute the log terms on both sides:

group like terms together:

divide through both sides by the coefficient on :

you can do some additional rewriting here using the properties of the logarithm to simplify things if you like: