A factory produces plate glass with a mean thickness of 4 mm and a standard deviation of 1.1 mm. A simple random sample of 100 sheets of glass is to be measured, and the mean thickness of the 100 sheets is to be computed. What is the probability that the average thickness of the 100 sheets is less than 3.74 mm

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 and standard deviation , the z-score of a measure X is given by:

In this problem:

The probability is the p-value of Z when X = 3.74, then:

By the Central Limit Theorem

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 link

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

the least value out of the data shown is 5, maybe if you post a picture with it i could a little more.

step-by-step explanation:

step-by-step explanation:

given that ab is divided into equal parts as

ac, cd, de, ef, fg, gh, hi, ib.

from this we find that f is the midpoint of ab.

so using mid point formula we find

f = (3,7)

similarly considering fb, we get

h = mid point of fb = ((6,6) and g, mid point of fh is

g = (9/2, 13/2)

i is mid point of hb

so i =(15/2,11/2)