Genetic Defects Data indicate that a particular genetic defect occurs in of every children. The records of a medical clinic show children with the defect in a total of examined. If the children were a random sample from the population of children represented by past records, what is the probability of observing a value of equal to or more?

Complete Question

The complete question is shown on the first uploaded image

The probability that there exist 60 or more defected children is

Looking at the value for this probability we see that it is not so small to the point that the observation of this kind would be a rare occurrence

Step-by-step explanation:

From the question we are told that

        in every 1000 children a particular genetic defect occurs to 1

        The number of sample selected is

The probability of observing the defect is mathematically evaluated as

The probability of not observing the defect is mathematically evaluated as

The mean of this probability is mathematically represented as

Substituting values

The standard deviation of this probability is mathematically represented as

Substituting values

 the probability of detecting   defects can be represented in as  normal distribution like

in standardizing the normal distribution the normal area used to approximate is the right of 59.5 instead of 60 because  x= 60 is part of the observation

The z -score is obtained mathematically as

The area to the left of z = 1.35 on the standardized normal distribution curve is 0.9099 obtained from the z-table shown z value to the left of the standardized normal curve

Note: We are looking for the area to the right i.e 60 or more

  The total area under the curve is 1

So

6mm^3 or .6cm^3

      216

      /   \

  36     6

  /   \     /

6     6   6

factor trees are nice.

85.560%

step-by-step explanation:

conditional probability is defined as:

p(a|b) = p(a∩b) / p(b)

in other words, the probability that a occurs, given that b has occurred = the probability that both a and b occur / the probability that b occurs.

in this example:

p(turns 64 | turns 44) = p(turns 64 & turns 44) / p(turns 44).

if someone turns 64, they must have already turned 44, so:

p(turns 64 | turns 44) = p(turns 64) / p(turns 44)

on page 42, we see that of the original 100,000, 94944 turn 44, and 81234 turn 64.   therefore:

p(turns 64 | turns 44) = 81234 / 94944

p(turns 64 | turns 44) = 0.85560