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Studentka2010 [4]
2 years ago
14

Watch help video

Mathematics
2 answers:
alexira [117]2 years ago
8 0

At he love that have been happy

Usimov [2.4K]2 years ago
6 0

Step-by-step explanation:

the basic probabilty of being born with that certain trait is 5/9.

that means the probabilty of being born without that certain trait is 1 - 5/9 = 4/9.

the probability of 2 children being born with that trait and 3 being born without that trait is

5/9 × 5/9 × 4/9 × 4/9 × 4/9

but as you can see, this only covers a specific case, e.g. when the first 2 children have the trait, and the younger siblings don't.

for the general probability of that questioned result we need to multiply this with the number of different combinations : in how many ways can I pick 2 children out of 5, when the sequence of the 2 picked children is irrelevant ?

this is C (5, 2) = 5!/((5-2)!×2) = 5!/(3!×2) = 5×4/2 = 5×2 = 10

so, the probability is

10×(5/9)²×(4/9)³ = 10×5²×4³/9⁵ = 0.270961405...

≈ 0.271

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A sales and marketing management magazine conducted a survey on salespeople cheating on their
Alenkinab [10]

Answer:

The 95% confidence interval estimate of the population proportion of managers who have caught salespeople cheating on an expense report is (0.5116, 0.6484).

Step-by-step explanation:

In a sample with a number n of people surveyed with a probability of a success of \pi, and a confidence level of 1-\alpha, we have the following confidence interval of proportions.

\pi \pm z\sqrt{\frac{\pi(1-\pi)}{n}}

In which

z is the zscore that has a pvalue of 1 - \frac{\alpha}{2}.

In the survey on 200 managers, 58% of the managers have caught salespeople cheating on an expense report.

This means that n = 200, \pi = 0.58

95% confidence level

So \alpha = 0.05, z is the value of Z that has a pvalue of 1 - \frac{0.05}{2} = 0.975, so Z = 1.96.

The lower limit of this interval is:

\pi - z\sqrt{\frac{\pi(1-\pi)}{n}} = 0.58 - 1.96\sqrt{\frac{0.58*0.42}{200}} = 0.5116

The upper limit of this interval is:

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The 95% confidence interval estimate of the population proportion of managers who have caught salespeople cheating on an expense report is (0.5116, 0.6484).

7 0
3 years ago
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