The birth weights of newborn babies in the United States follow a normal distribution with a mean of 3.4 kg and a standard deviation of 0.6 kg. Researchers interested in studying how children gain weight decide to take random samples of 100 newborn babies and calculate the sample mean birth weight for each sample. Calculate the mean and standard deviation of the sampling distribution

Using the Central Limit Theorem, it is found that:

In this problem:

Hence, the mean of the sampling distribution is of 3.4 kg and the standard deviation is of 0.06 kg.

To learn more about the Central Limit Theorem, you can take a look at link

3.4 kg

0.06 kg

Step-by-step explanation:

Given that:

Birthweight follows a normal distribution :

Mean weighf (m) = 3.4 kg

Standard deviation (σ) = 0.6 kg

Sample size (n) = 100 new born babies

calculate the sample mean birth weight for each sample. Calculate the mean and standard deviation of the sampling distribution

The sample mean birth weight = population mean birth weight for a normal distribution according to the central Limit theorem.

Hence, sample mean birth weight = 3.4kg

Standard deviation of sampling distribution = standard error = σ/√n

0.6 / √100

= 0.6 / 10

= 0.06 kg

x = 17

step-by-step explanation:

1st step: isolate x.

24 - 3x = -27

-24         -24

-3x   =   -51

2nd step: divide.

-3x     =   -51

  3             3

  x       =     17

hope this

geometry: triangles

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call the larger triangle abc

then the smaller triangle cde is similar to abc (all angles are equal, aaa).  

ab is the side that is 36, and we wish to find de, the side corresponding to ab

area_cde = area_abc - area_cde --> area_abc / area_cde = 2

let x=length of de

ratio of areas = (ratio of sides)^2

+2+=+%2836%2fx%29%5e2+

+2+=+1296%2fx%5e2+

++x%5e2+=+1296%2f2+=+648+

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