In a carnival, there is a game of chance. A player should throw a die. If a composite number is obtained, he wins Php 45.00. Otherwise, he loses Php 15.00. If a player continues to play the game, what is the player's expected gain/loss?? Php 25.00 Php 15.00 Php 5.00 Php 35.00 What is the standard deviation of the said distribution? Php 800.00 Php 14.14 Php 28.28 Php 200.00
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!
In a carnival, there is a game of chance. A player should throw a die. If a composite number is obtained, he wins Php 45.00. Otherwise, he loses Php 15.00.
If a player continues to play the game, what is the player's expected gain/loss??
- Php 25.00
- Php 15.00
- Php 5.00
- Php 35.00
What is the standard deviation of the said distribution?
- Php 800.00
- Php 14.14
- Php 28.28
- Php 200.00
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