The average score for games played in the NFL is 21 and the standard deviation is 9.3 points. 45 games are randomly selected. Round all answers to 4 decimal places where possible and assume a normal distribution. a. What is the distribution of ¤? ¤ - N( b. What is the distribution of >x? ) x - N( c. P(ī < 22.8204) =
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!
The average score for games played in the NFL is 21 and the standard deviation is 9.3 points. 45 games are randomly selected. Round all answers to 4 decimal places where possible and assume a
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- Multiple normal distribution: If X1,X2,X3,...,Xn > 0 are mutually independent normal random variables with means μ1,μ2,μ3,...,μn and variances σ21 ,σ22 ,σ23 ,...,σ2n μ1,μ2,μ3,...,μn and variances σ12 ,σ22 ,σ32 ,...,σn2, then the linear combination:
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