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2 answers:
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Answer:
By the Central Limit Theorem, both would be approximately normal and have the same mean. The difference is in the standard deviation, since as the sample size increases, the standard deviation decreases. So the SRS of 600 would have a smaller standard deviation than the SRS of 200.
Step-by-step explanation:
The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean and standard deviation
, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean
and standard deviation
.
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.
For the sampling distribution of size n of a sample proportion p, the mean is p and the standard deviation is
Differences between SRS of 200 and of 600
By the Central Limit Theorem, both would be approximately normal and have the same mean. The difference is in the standard deviation, since as the sample size increases, the standard deviation decreases. So the SRS of 600 would have a smaller standard deviation than the SRS of 200.
Answer:
The probability that at lest one job will be missed in 57 second is =0.819134
Step-by-step explanation:
Poisson distribution:
A discrete random variable X having the enumerable set {0,1,2,....} as the spectrum, is said to be Poisson distribution.
for x=0,1,2...
λ is the average per unit time
Given that, a job arrives at a web server with the probability 0.03.
Here λ=0.03, t=57 second.
The probability that at lest one job will be missed in 57 second is
=P(X≥1)
=1- P(X<1)
=1- P(X=0)
=0.819134