Question

The certain paper suggested that a normal distribution with mean 3,500 grams and standard deviation 560 grams is a reasonable model for birth weights of babies born in Canada. (You may need to use a table Round your answers to four decimal places.) A USE SALT

(a) One common medical definition of a large baby is any baby that weighs more than 4,000 grams at birth. What is the probability that a randomly selected Canadian baby is a large baby? 186
(b) What is the probability that a randomly selected Canadian baby weighs either less than 2.000 grams or more than 4,000 grams at birth? D ( What birth weights describe the 25of Canadian babies with the greatest birth weights? Any taby with a weight of 43752 x grams of more is in the greatest 2 of birth weights

Answer 1

To find the probability of a randomly selected Canadian baby being large, we use the normal distribution. By converting the weight of 4,000 grams to a z-score, we can find the corresponding probability. The probability is approximately 0.8132.

Step-by-step explanation:

To find the probability that a randomly selected Canadian baby is a large baby, we need to find the area under the normal distribution curve to the right of 4,000 grams. Since we are given the mean (3,500 grams) and standard deviation (560 grams), we can convert the value of 4,000 grams to a z-score using the formula:

z = (x - μ) / σ

where z is the z-score, x is the value we want to convert, μ is the mean, and σ is the standard deviation.

Substituting the given values, we have:

z = (4,000 - 3,500) / 560 = 0.8929

Using the z-score table or a calculator, we can find that the probability corresponding to a z-score of 0.8929 is approximately 0.8132.

Therefore, the probability that a randomly selected Canadian baby is a large baby (weighs more than 4,000 grams) is approximately 0.8132.