Normal Distribution Samples

In summary: The answer is: There is a probability of 0.5 (50% chance) of getting at least 4 heads in 5 coin tosses.
  • #1
DotFourier
2
0

Homework Statement


Suppose that diastolic blood pressures (DBPs) for men aged 35-44 are normally distributed with a mean of 80 (mm Hg) and a standard deviation of 10. What's the probability that in a random sample of 5 subjects, 4 or more have DBPs more than 90?

Homework Equations

The Attempt at a Solution


I first thought of finding the probability that someone from the sample of 5 has DBP greater than 90. After converting to standard normal and looking at a Z table I found that it was 0.0125. I do not know where to go from here. I am confused as to what to do to be able to find the probability of 4 or more having more than 90 DBP.
 
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  • #2
DotFourier said:

Homework Statement


Suppose that diastolic blood pressures (DBPs) for men aged 35-44 are normally distributed with a mean of 80 (mm Hg) and a standard deviation of 10. What's the probability that in a random sample of 5 subjects, 4 or more have DBPs more than 90?

Homework Equations

The Attempt at a Solution


I first thought of finding the probability that someone from the sample of 5 has DBP greater than 90. After converting to standard normal and looking at a Z table I found that it was 0.0125. I do not know where to go from here. I am confused as to what to do to be able to find the probability of 4 or more having more than 90 DBP.
Start by finding the probability that 1 person has DBP > 90. I would say ##.0125## looks way too small. How did you get that?
 
  • #3
Once you have the right probability for one sample, then you can use a combinatorial approach.
Let p(x) be the probability that anyone sample has DBP>90 and p(~x) be the probability of not that.
p(~x)=1-p(x).
Choose 5 people at random, there are ##\begin{pmatrix} 5\\4\end{pmatrix} ## ways to get 4 people with high blood pressure, and the number of ways to have 4 or more is slightly greater than that.
You could use a probability tree, but that would take a long time.

You could also enumerate all the options and find the probability of each case:
X1 = x, x, x, x, x (5 people have high BP) , p(X1) = ?
x, x, x, x, ~x (4 people have high BP)
.
.
.
~x, x, x, x, x (4 people have high BP)
The total probability is the sum of the independent cases.

However, using the fact that you can know how many cases of each type there might be, and the relative similarity of the probability profile for each case, you can simplify this down to a quick and easy function of p(x).
 
  • #4
DotFourier said:

Homework Statement


Suppose that diastolic blood pressures (DBPs) for men aged 35-44 are normally distributed with a mean of 80 (mm Hg) and a standard deviation of 10. What's the probability that in a random sample of 5 subjects, 4 or more have DBPs more than 90?

Homework Equations

The Attempt at a Solution


I first thought of finding the probability that someone from the sample of 5 has DBP greater than 90. After converting to standard normal and looking at a Z table I found that it was 0.0125. I do not know where to go from here. I am confused as to what to do to be able to find the probability of 4 or more having more than 90 DBP.

This is like a coin-tossing problem, but with a biased coin having ##P(\text{heads}) = p##. Here, ##p## is the probability that an individual has DBP > 90; you claimed that ##p = 0.0125## but that is not so. Anyway, for any value of ##p## (whether correct or not) you now ask: if you toss your biased coin 5 times, what is the probability of getting at least 4 heads? Getting a 'head' in a toss is like an individual having DBP > 90, so that is really the same question as the one you are asked. Surely you have seen similar coin-tossing probability problems in the past?
 

1. What is a normal distribution sample?

A normal distribution sample is a set of data points that follow a bell-shaped curve when plotted on a graph. It is characterized by a symmetrical distribution around the mean, with most values falling near the center and fewer values towards the tails of the curve.

2. How is a normal distribution sample different from other types of distributions?

A normal distribution sample differs from other types of distributions in that it follows a specific mathematical formula known as the normal distribution, also called the Gaussian distribution. Other distributions, such as the uniform distribution or the exponential distribution, have different shapes and follow different mathematical formulas.

3. What are the properties of a normal distribution sample?

The properties of a normal distribution sample include a symmetric shape, where the mean, median, and mode are all equal, and the curve is centered around the mean. Additionally, approximately 68% of data points fall within one standard deviation of the mean, 95% fall within two standard deviations, and 99.7% fall within three standard deviations.

4. How can a normal distribution sample be used in statistics?

A normal distribution sample is commonly used in statistics to model real-world phenomena, as many natural phenomena tend to follow a normal distribution. It is also used in hypothesis testing, as it allows for the calculation of probabilities and confidence intervals.

5. Can a sample deviate from a normal distribution?

Yes, a sample can deviate from a normal distribution. In fact, it is rare for a sample to perfectly follow a normal distribution, and slight deviations are expected. These deviations can be caused by various factors, such as sampling error, outliers, or underlying population distributions that are not normal.

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