At Westonci.ca, we connect you with the answers you need, thanks to our active and informed community. Experience the ease of finding precise answers to your questions from a knowledgeable community of experts. Connect with a community of professionals ready to help you find accurate solutions to your questions quickly and efficiently.

(1) The scores ou an aptitude test for finger dexterity are uonually distributed with meau 250 and
standard deviation 65.
a) What is the probability that a person selected at random will score between 240 and 270 on the
test?
b) Test is given to a random sample of seven people. What is the probability that the mean score,
I for the sample will be between 240 and 270?


Sagot :

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

a) 0.1813 = 18.13% probability that a person selected at random will score between 240 and 270 on the test.

b) 0.4501 = 45.01% probability that the mean score for the sample will be between 240 and 270.

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.
  • By the Central Limit Theorem, the sampling distribution of sample means of size n has standard deviation [tex]s = \frac{\sigma}{\sqrt{n}}[/tex].

In this problem:

  • The mean is of [tex]\mu = 250[/tex].
  • The standard deviation is of [tex]\sigma = 65[/tex].

Item a:

The probability is the p-value of Z when X = 270 subtracted by the p-value of Z when X = 240, hence:

X = 270:

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

[tex]Z = \frac{270 - 250}{65}[/tex]

[tex]Z = 0.31[/tex]

[tex]Z = 0.31[/tex] has a p-value of 0.6217.

X = 240:

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

[tex]Z = \frac{240 - 250}{65}[/tex]

[tex]Z = -0.15[/tex]

[tex]Z = -0.15[/tex] has a p-value of 0.4404.

0.6217 - 0.4404 = 0.1813.

0.1813 = 18.13% probability that a person selected at random will score between 240 and 270 on the test.

Item b:

We have a sample of 7, hence:

[tex]n = 7, s = \frac{65}{\sqrt{7}} = 24.57[/tex]

X = 270:

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

By the Central Limit Theorem

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

[tex]Z = \frac{270 - 250}{24.57}[/tex]

[tex]Z = 0.81[/tex]

[tex]Z = 0.81[/tex] has a p-value of 0.7910.

X = 240:

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

[tex]Z = \frac{240 - 250}{24.57}[/tex]

[tex]Z = -0.41[/tex]

[tex]Z = -0.41[/tex] has a p-value of 0.3409.

0.7910 - 0.3409 = 0.4501.

0.4501 = 45.01% probability that the mean score for the sample will be between 240 and 270.

To learn more about the normal distribution and the central limit theorem, you can check https://brainly.com/question/24663213