Probability of Height in Poor Countries: 94-112cms

In summary, the growth of children in poor countries can be indicative of their nutrition and health levels. Studies show that the height of a randomly selected 5 year old child can be modeled using a normal distribution with mean 100 cms and standard deviation 6 cms. The proportion of height between 94 and 112 cms is 0.4544, the probability of a child being taller than 110 cms is 0.0228, and the probability of exactly one of two children being taller than 110 cms is 0.0211.
  • #1
sumans
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In poor countries, the growth of children can be an important indicator of general levels of nutrition and health. Data from several studies suggest that a reasonable model for the probability distribution of the height (in cms) of a randomly selected 5 year old child is normally distributed with mean 100 cms and standard deviation 6 cms.

a) What proportion of height is between 94 and 112 cms?
b) What is the probability that a random chosen five year old child will be taller than 110 cms.
c) If two five-year old children are drawn at random, what is the probability that exactly one of them will be taller than 110 cms.

It is given that area under a standard normal distribution between z = 0 and given values of z are as follows:
For z = 1.00 area = 0.3413
For z = 1.67 area = 0.4523
For z = 2.00 area = 0.4772
 
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  • #2
For z = 2.33 area = 0.4983a) The proportion of height between 94 and 112 cm is the area under the normal curve between z = -2 and z = 2, which is equal to 0.4772 - 0.0228 = 0.4544. b) The probability that a random chosen five year old child will be taller than 110 cms is the area under the normal curve between z = 2 and z = infinity, which is equal to 0.4772 - 0.5 = 0.0228. c) The probability that exactly one of two randomly chosen five-year old children will be taller than 110 cms is the area under the normal curve between z = 2 and z = 2.33, which is equal to 0.4983 - 0.4772 = 0.0211.
 
  • #3


a) The proportion of height between 94 and 112 cms can be found by calculating the z-scores for these values and then finding the area under the curve between these z-scores. The z-scores for 94 and 112 are -1 and +2 respectively. Using the given values for area under the curve, we can find the area between these z-scores as follows:

Area = 0.4772 - 0.3413 = 0.1359 or 13.59%

Therefore, approximately 13.59% of children in poor countries have a height between 94 and 112 cms.

b) To find the probability that a randomly chosen five year old child will be taller than 110 cms, we first need to find the z-score for 110 cms. This can be calculated as:

z = (110 - 100)/6 = 1.67

Using the given values for area under the curve, we can find the area to the right of this z-score as follows:

Area = 0.5000 - 0.4523 = 0.0477 or 4.77%

Therefore, there is a 4.77% probability that a randomly chosen five year old child will be taller than 110 cms.

c) The probability that exactly one of the two children will be taller than 110 cms can be calculated by finding the area under the curve for one child being taller than 110 cms and the other being shorter than 110 cms. This can be calculated as:

Area = (0.5000 - 0.4523) x (0.5000 - 0.4523) = 0.0228 or 2.28%

Therefore, there is a 2.28% probability that exactly one of the two children drawn at random will be taller than 110 cms.
 

FAQ: Probability of Height in Poor Countries: 94-112cms

What is the significance of studying the probability of height in poor countries?

The probability of height in poor countries is an important factor to consider in understanding the overall health and well-being of individuals living in these countries. It can also provide insight into the impact of poverty and malnutrition on physical growth and development.

How is the probability of height measured in poor countries?

The probability of height is typically measured through data collection and analysis of height measurements from a representative sample of individuals living in poor countries. This data is then used to calculate the likelihood of individuals falling within a certain height range, such as 94-112cms.

What factors can influence the probability of height in poor countries?

There are several factors that can influence the probability of height in poor countries, including access to adequate nutrition, healthcare, and sanitation. Socioeconomic factors, such as poverty and inequality, can also play a significant role in determining the height probability of individuals in these countries.

How does the probability of height in poor countries compare to that of developed countries?

The probability of height in poor countries is typically lower than that of developed countries, due to the impact of poverty and its associated factors on physical growth and development. However, it is important to note that there can also be significant variations in height probability among different regions and communities within poor countries.

Can the probability of height in poor countries be improved?

Yes, the probability of height in poor countries can be improved through various interventions, such as improving access to nutritious food, healthcare, and education. Addressing issues of poverty and inequality can also have a positive impact on height probability in these countries.

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