Respuesta :
Answer:
0.0090483
Approximately = 0.00905
Step-by-step explanation:
z = (x - μ)/σ, where
x is the raw score = 3.74
μ is the sample mean = population mean = 4 mm
σ is the sample standard deviation
This is calculated as:
= Population standard deviation/√n
Where n = number of samples = 100
σ = 1.1/√100
σ = 1.1/10 = 0.11
z = (3.74 - 4) / 0.11
z = -2.36364
Using the z score table to determine the probability,
The probability that the average thickness of the 100 sheets is less than 3.74 mm
P(x<3.74) = 0.0090483
Approximately = 0.00905
Using the normal distribution and the central limit theorem, it is found that there is a 0.0091 = 0.91% probability that the average thickness of the 100 sheets is less than 3.74 mm.
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. Â
- 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 for size n has standard deviation [tex]s = \frac{\sigma}{\sqrt{n}}[/tex].
In this problem:
- Mean thickness of 4 mm, thus [tex]\mu = 4[/tex].
- Standard deviation of 1.1 mm, thus [tex]\sigma = 1.1[/tex].
- Sample of 100, thus [tex]n = 100, s = \frac{1.1}{\sqrt{100}} = 0.11[/tex].
The probability is the p-value of Z when X = 3.74, then:
[tex]Z = \frac{X - \mu}{\sigma}[/tex]
By the Central Limit Theorem
[tex]Z = \frac{X - \mu}{s}[/tex]
[tex]Z = \frac{3.74 - 4}{0.11}[/tex]
[tex]Z = -2.36[/tex]
[tex]Z = -2.36[/tex] has a p-value of 0.0091.
0.0091 = 0.91% probability that the average thickness of the 100 sheets is less than 3.74 mm.
A similar problem is given at https://brainly.com/question/14228383
