"A waiter believes the distribution of his tips has a model that is slightly skewed to the left​, with a mean of ​$10.60 and a standard deviation of ​$6.60. He usually waits on about 50 parties over a weekend of work. ​a) Estimate the probability that he will earn at least ​$600. ​b) How much does he earn on the best 1​% of such​ weekends?"

Answers

Answer 1

Answer:

(a) 0.0668

(b) $638.74

Step-by-step explanation:

Let X denote the tips earned by a waiter.

It is provided that X follows a left-skewed distribution with mean, μ = $10.60 and standard deviation, σ = $6.60.

It is also provided that, the waiter usually waits on about n = 50 parties over a weekend of work.

According to the Central Limit Theorem if we have a population with mean μ and standard deviation σ and we take appropriately huge random samples (n ≥ 30) from the population with replacement, then the distribution of the sum of values of X, i.e ∑X, will be approximately normally distributed.  

Then, the mean of the distribution of the sum of values of X is given by,  

 [tex]\mu_{S}=n\mu\\[/tex]

And the standard deviation of the distribution of the sum of values of X is given by,  

[tex]\sigma_{S}=\sqrt{n}\sigma[/tex]

As the sample size is large, i.e. n = 50 > 30, the Central Limit Theorem can be used to approximate the sampling distribution of total tips by the normal distribution.

The mean and standard deviation are:

[tex]\mu_{S}=50\times 10.60=530\\\\\sigma_{S}=\sqrt{50}\times 6.60=46.67[/tex]

(a)

Compute the probability that he will earn at least $600 as follows:

[tex]P(S\geq 600)=P(\frac{S-\mu_{S}}{\sigma_{S}}\geq \frac{600-530}{46.67})\\\\=P(Z>1.50)\\\\=1-P(Z<1.50)\\\\=1-0.93319\\\\=0.06681\\\\\approx 0.0668[/tex]

Thus, the probability that he will earn at least $600 is 0.0668.

(b)

Let x represents his earnings on the best 1%  of such weekends.

That is, P (X < x) = 0.99.

⇒ P (Z < z) = 0.99

The corresponding z-score is, 2.33.

Compute the value of x as follows:

[tex]z=\frac{S-\mu_{S}}{\sigma_{S}}\\\\2.33=\frac{x-530}{46.67}\\\\x=530+(2.33\times 46.67)\\\\x=638.7411\\\\x\approx 638.74[/tex]

Thus, on the best 1%  of such weekends the waiter earned $638.74.


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Step-by-step explanation:

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Answers

Answer:

0.8809

Step-by-step explanation:

Given that:

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The sample size n = 300

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= 16/300

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[tex]P(\hat p \leq 0.0533) = P\bigg ( \dfrac{\hat p - p}{\sqrt{\dfrac{P(1-P)}{n}}}\leq\dfrac{0.0533 - 0.04}{\sqrt{\dfrac{0.04(1-0.04)}{300}}}\bigg )[/tex]

[tex]P(\hat p \leq 0.0533) = P\bigg ( Z\leq\dfrac{0.0133}{\sqrt{\dfrac{0.04(0.96)}{300}}}\bigg )[/tex]

[tex]P(\hat p \leq 0.0533) = P\bigg ( Z\leq\dfrac{0.0133}{\sqrt{\dfrac{0.0384}{300}}}\bigg )[/tex]

[tex]P(\hat p \leq 0.0533) = P\bigg ( Z\leq\dfrac{0.0133}{\sqrt{1.28 \times 10^{-4}}}\bigg )[/tex]

[tex]P(\hat p \leq 0.0533) = P\bigg ( Z\leq\dfrac{0.0133}{0.0113}}\bigg )[/tex]

[tex]P(\hat p \leq 0.0533) = P\bigg ( Z\leq1.18}\bigg )[/tex]

From the z tables;

= 0.8809

OR

Let X be the random variation that follows a normal distribution;

Then;

population mean [tex]\mu[/tex] = n × p

population mean [tex]\mu[/tex] = 300 × 0.04

population mean [tex]\mu[/tex] = 12

The standard deviation [tex]\sigma = \sqrt{np(1-p)}[/tex]

The standard deviation  [tex]\sigma = \sqrt{300 \times 0.04(1-0.04)}[/tex]

The standard deviation [tex]\sigma = \sqrt{11.52}[/tex]

The standard deviation  [tex]\sigma = 3.39[/tex]

The z -score can be computed as:

[tex]z = \dfrac{x - \mu}{\sigma}[/tex]

[tex]z = \dfrac{16 -12}{3.39}[/tex]

[tex]z = \dfrac{4}{3.39}[/tex]

z = 1.18

The required probability is:

P(X ≤ 10) = Pr (z  ≤ 1.18)

= 0.8809

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Answers

Answer:

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Step-by-step explanation:

We can subtract to find the amount of men who took the survey.

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Required:
a. Construct a 95â% confidence interval to estimate of the percentage of yellow peas.
b. It was expected thatâ 25% of the offspring peas would be yellow. Given that the percentage of offspring yellow peas is notâ 25%, do the results contradictâ expectations?

Answers

Answer:

a

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b

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Step-by-step explanation:

From the question we are told that

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Answers

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Step-by-step explanation:

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Answers

Answer:

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Step-by-step explanation:

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Hope this Helps!!

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