And unfair coin lands head up with a probability of 0.4 when it is flipped. John has been asked to flip this coin twice in succession and told that he will win seven dollars if both flips landed up. John was also told that if just one flip lands head up then he will win 4$, while if none land head up he will win nothing.
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
And unfair coin lands head up with a probability of 0.4 when it is flipped. John has been asked to flip this coin twice in succession and told that he will win seven dollars if both flips landed up. John was also told that if just one flip lands head up then he will win 4$, while if none land head up he will win nothing.
Let E[x] be The random variable that represents the amount of money John can win in this activity.
What is E[X]?
a. $2.92
b. $3.04
c. $3.88
d. $2.88
e. $3.51
f. None of the above
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