Providence, RI has the best donuts in the U.S., it’s no question! Consider the following pdfs regarding the two competing bakeries in Providence. Let the random variables
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
Providence, RI has the best donuts in the U.S., it’s no question! Consider the following pdfs regarding the two competing bakeries in Providence. Let the random variables X and Y represent the number of donuts produced per hour in which the donut hole was not punched out for bakery X and bakery Y, respectively.
|
X,Y |
0 |
1 |
2 |
3 |
4 |
5 |
|
P(x) |
.91 |
.04 |
.01 |
.02 |
.01 |
.01 |
|
P(y) |
.67 |
.21 |
.04 |
.05 |
.01 |
.02 |
Given that by 12:30pm (i.e. within the last 30 minutes of the current “hour”) bakery Y has produced 1 donut in which the donut hole was not punched out, what is the
a.) 24%
b.) 9%
c.) 14%
d.) 22%
e.) 50%
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