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A fair spinner has 9 equal sections: 3 red, 2 blue and 4 green.

It is spun twice.

What is the probability of not getting two consecutive blues?


Assume that we are estimating the population mean with confidence level 1 when the population standard deviation is known. Then UCL LCL D 2 B where LCL is the lower confidence limit, UCL is the upper confidence limit and B is the limit on the error of estimation. True or False.

A survey of 1000 men ages 20 to 30 found that their heights were normally distributed, with a mean of 65 inches and a standard deviation of 2.5 inches. How many men have a height that is within 1 standard deviation of the mean?


If the probability that a florescent light has a useful life of at least 800 hours is 0.9,
find the probabilities that among 20 such lights
(a). exactly 18 will have a useful life of at least 800 hours;
(b). exactly 15 will have a useful life of at least 800 hours;
(c). at least 2 will not have a useful life of at least 800 hours;
show that if (A/B)=1, then P(B^c/A^c)= 1
  1. If 𝑋~𝑑(π‘˜) , then 𝐸[𝑋] = 0 if π‘˜ > 1 and π‘‰π‘Žπ‘Ÿ[𝑋] = π‘˜ π‘˜βˆ’2 if k >2
  2. If X is an F – distributed random variable with m and n degrees of freedom, then π‘‰π‘Žπ‘Ÿ[𝑋] = (2𝑛^2(π‘š+π‘›βˆ’2))/(π‘š(π‘›βˆ’2)^2(π‘›βˆ’4)).
  3. If X has a chi-square distribution, then π‘šπ‘‹(𝑑) = [ (1/2)/((1/ 2)βˆ’π‘‘ )] ^(π‘˜/2) = [ (1)/(1βˆ’2𝑑) ] ^(π‘˜/2) , t < Β½.

a large population consist of equal numbers of the digits 1 and 3. (a) Find the mean and variance of this population (b) Find the probability distribution of the mean of samples size three taken from this population and verify that this mean mean is equal to the population mean and its variance is equal to one-third of theΒ  population variance


Let A and B be events such that P(A) = 0.6, P(A È B) = 0.8 and P(A | B) = 0.6.

Find P(B).



You visit a meat shop and asked the seller about the total weight of meat sold in a single day. If this is a random variable, what are the possible values of this variable?

Suppose a production facility purchases a particular component part in large lots from a

supplier. The production manager wants to estimate the proportion of defective parts

received from this supplier. She believes the proportion defective is no more than .20 and

wants to be within .02 of the true proportion of defective parts with a 90% level of

confidence. How large a sample should she take?


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