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Ronch [10]
3 years ago
11

Suppose there are 6 runners in the finals of a 100 m sprint, Abbie, Becca, Clarice, Danna, Emma, and Francine. Answer each of th

e following questions.
1. An analyst, Grace, gives Abbie a 12% chance to place first and Becca an 8% chance to place second. Assume these percentages are accurate. Can we determine the probability that Abbie will place first and Becca will place second? Why or why not?

2. Grace further informs us that the two favorites to win the race are Danna and Francine. Grace gives Danna a 48% chance to win the race and Francine a 32% chance to win. Assume these percentages are accurate. Find the probability that Danna or Francine wins the race, if possible. If not possible, explain why.

3. Suppose Abbie places first. Does this mean that Grace's probabilities were wrong? Justify your answer using terms and reasoning discussed in Chapter 5.

Bonus: Can we determine who Grace thinks is third most likely to win the race? If so, who?
Mathematics
1 answer:
Lilit [14]3 years ago
6 0

Answer:

grace will not win the race because she is to slow thanks and I would appriciate if i got brainlies i just need one more crown

Step-by-step explanation:

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Answer:

The probability hat the sample mean height for the 40 chimneys is greater than 102 meters is 0.1469.

Step-by-step explanation:

Let the random variable <em>X</em> be defined as the height of chimneys in factories.

The mean height is, <em>μ</em> = 100 meters.

The standard deviation of heights is, <em>σ</em> = 12 meters.

It is provided that a random sample of <em>n</em> = 40 chimney heights is obtained.

According to the Central Limit Theorem if we have an unknown population with mean <em>μ</em> and standard deviation <em>σ</em> and appropriately huge random samples (<em>n</em> > 30) are selected from the population with replacement, then the distribution of the sample means will be approximately normally distributed.

Then, the mean of the distribution of sample means is given by,

\mu_{\bar x}=\mu

And the standard deviation of the distribution of sample means is given by,

\sigma_{\bar x}=\frac{\sigma}{\sqrt{n}}

Since the sample selected is quite large, i.e. <em>n</em> = 40 > 30, the central limit theorem can be used to approximate the sampling distribution of sample mean heights of chimneys.

\bar X\sim N(\mu_{\bar x},\ \sigma^{2}_{\bar x})

Compute the probability hat the sample mean height for the 40 chimneys is greater than 102 meters as follows:

P(\bar X>102)=P(\frac{\bar X-\mu_{\bar x}}{\sigma_{\bar x}})>\frac{102-100}{12/\sqrt{40}})

                    =P(Z>1.05)\\=1-P(Z

*Use a <em>z</em>-table fr the probability.

Thus, the probability hat the sample mean height for the 40 chimneys is greater than 102 meters is 0.1469.

8 0
3 years ago
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