Please help with part eh I am using a ti83 calculator so ple
Please help with part e-h. I am using a ti83 calculator, so please give the commands that you used so I can check the work!
There is some evidence to suggest that businesses are moving out of states where unions are prevalent. In California, 18.4% of all workers belong to a union. Suppose 26 workers from California are selected at random. 3. a. Demonstrate that X the number of workers that belong to a union is a binomial random variable. Find the following probabilities: b. At most three California workers belong to a union c. At least four but at most seven California workers belong to a union d. Exactly eight California workers belong to a union. Less than twenty California workers do not belong to a union. e. 2) e. More than nine but at most fourteen California workers do not belong to a union. f. What is the mean number of California workers that do belong to a union? Use the correct notation g. What is the standard deviation for this probability distribution? Use the correct notation h. Find P(-2Solution
e)
Here, n = 26, p = 1 - 0.184 = 0.816, as we refer to those who are not members of a union.
Note that P(fewer than x) = P(at most x - 1).
Using a cumulative binomial distribution table or technology, matching
n = number of trials = 26
p = the probability of a success = 0.816
x = our critical value of successes = 20
Then the cumulative probability of P(at most x - 1) from a table/technology is
P(at most 19 ) = 0.18846503
[You can do this part by doing binomcdf(26,0.816,20)]
Which is also
P(fewer than 20 ) = 0.18846503
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e) [There are two e\'s!]
Note that P(between x1 and x2) = P(at most x2) - P(at most x1 - 1)
Here,
x1 = 10
x2 = 14
Using a cumulative binomial distribution table or technology, matching
n = number of trials = 26
p = the probability of a success = 0.816
Then
P(at most 9 ) = 1.7898E-07
[binomcdf(26,0.816,9)]
P(at most 14 ) = 0.001101006
[binomcdf(26,0.816,14)]
Thus,
P(between x1 and x2) = 0.001100827 [ANSWER]
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f)
mean = n p = 26*0.184 = 4.784 [answer]
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g)
standard deviation = sqrt(n p (1-p)) = sqrt(26*0.184*(1-0.184)) = 1.975789462 [ANSWER]
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h)
By empirical rule, within 2 standard deviations from the mean has probability 0.9545. [ANSWER]

