At a new exhibit in the Museum of Science, people are asked to choose between 73 or 175 random draws from a machine. The machine is known to have 98 green balls and 61 red balls. After each draw, the color of the ball is noted and the ball is put back for the next draw. You win a prize if more than 70% of the draws result in a green ball. [You may find it useful to reference the z table.] a. Calculate the probability of getting more than 70% green balls. (Round your intermediate proportion values and “z” value to 2 decimal places, and final answer to 4 decimal places.) b. Would you choose 73 or 175 draws for the game?

Respuesta :

Answer:

Probability of winning first situation:  0.0793

Probability of winning second situation:  0.0146

You should go with the first option

Step-by-step explanation:

See attached photo for answers.   For this situation you need to identify p-hat, p, q and n.

P-hat, p, and q all stay the same for both situations, only n changes.

p-hat is the proportion of green balls we want, which is 0.7

p = 98/159 = 0.62

q = 0.38 because q = 1 - p, which in this case is q = 1 - 0.62 = 0.38

n = 73 for the first situation, and n = 175 for the second situation

Ver imagen MrSmoot

Using the normal probability distribution and the central limit theorem, it is found that:

a)

With 73 draws, there is a 0.0808 = 8.08% probability of getting more than 70% green balls.

With 175 draws, 0.015 = 1.5% probability of getting more than 70% green balls.

b)

Due to the higher probability of getting more than 70% green balls, 73 draws should be chosen.

Normal Probability Distribution

In a normal distribution with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the z-score of a measure X is given by:

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

  • It measures how many standard deviations the measure is from the mean.  
  • After finding the z-score, we look at the z-score table and find the p-value associated with this z-score, which is the percentile of X.  

Central Limit Theorem

  • It states that the sampling distribution of the sample means with size n can be approximated to a normal distribution.
  • For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean [tex]\mu = p[/tex] and standard deviation [tex]s = \sqrt{\frac{p(1-p)}{n}}[/tex]

Item a:

  • 98 green balls out of 158, thus [tex]p = \frac{98}{158} = 0.6203[/tex]

Out of 73 draws:

[tex]s = \sqrt{\frac{p(1-p)}{n}} = \sqrt{\frac{0.6203(0.3797)}{73}} = 0.0568[/tex]

The probability of more than 70% green balls is 1 subtracted by the p-value of Z when X = 0.7, thus:

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

By the Central Limit Theorem

[tex]Z = \frac{X - \mu}{s}[/tex]

[tex]Z = \frac{0.7 - 0.6203}{0.0568}[/tex]

[tex]Z = 1.4[/tex]

[tex]Z = 1.4[/tex] has a p-value of 0.9192.

1 - 0.9192 = 0.0808

With 73 draws, there is a 0.0808 = 8.08% probability of getting more than 70% green balls.

Out of 175 draws:

[tex]s = \sqrt{\frac{p(1-p)}{n}} = \sqrt{\frac{0.6203(0.3797)}{175}} = 0.0367[/tex]

Then:

[tex]Z = \frac{X - \mu}{s}[/tex]

[tex]Z = \frac{0.7 - 0.6203}{0.0367}[/tex]

[tex]Z = 2.17[/tex]

[tex]Z = 2.17[/tex] has a p-value of 0.985.

1 - 0.985 = 0.015.

With 175 draws, 0.015 = 1.5% probability of getting more than 70% green balls.

Item b:

Due to the higher probability of getting more than 70% green balls, 73 draws should be chosen.

A similar problem is given at https://brainly.com/question/24663213