The Normal Distribution and Discrete Populations

In summary, the given conversation discusses the use of continuity correction in approximating probabilities using the normal distribution, specifically in the context of a binomial distribution being treated as a normal distribution. It also involves finding the median of a normal distribution, which is equal to the mean.
  • #1
Shoney45
68
0

Homework Statement

One sixth of the male freshman entering a large state school are out of state students. If the students are assigned at random to the formitories, 180 to a building.

1) What approximately is the probability that in a given dormitory at least one fifth of the students are from out of state? (Hint Continuity Correction)

2) What approximately, is the median of the number of the out of state students in a given dormitory?



Homework Equations


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The Attempt at a Solution

The part I am unsure of has to do with the 'continuity correction'. My book gives the impression on the page prior to introducing this formula that continuity correction has to do with subtracting .5 from the value of x.

The explanation for this comes from a section titled 'The Normal Distribution and Discrete Populations'. It says that because the rectangles of a histogram are centered at integers, the rectangle representing 36 actually begins at 35.5. So I am unsure if I should plug in 36, or 35.5 into the formula.
 
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  • #2
A binomial distribution is discrete while the normal distribution is continuous.

So say you wanted to find P(X≥1), you can use the distribution and find. If you approximated it with the normal, then values more than 0.5 you call as 1.

So 0.6 can be approximated to 1, 0.7 and so forth.

So to use the normal distribution, you'll want to find P(X>0.5) and then apply the transform Z=(X-μ)/σ.

Does it make a little more sense now?

So in your question you want P(X≥36), if you want to use the normal distribution, what probability do you want P(?)
 
  • #3
rock.freak667 said:
...to use the normal distribution, you'll want to find P(X>0.5) and then apply the transform Z=(X-μ)/σ.

So in your question you want P(X≥36), if you want to use the normal distribution, what probability do you want P(?)

Does it make a little more sense now?

Okay, so since I am looking for P(X≥36), and since that rectangle on the histogram goes from 35.5 - 36.5, then I think you're saying that I need to Z=[(X-μ)/σ] = (35.5 - μ)/σ.
 
  • #4
Now I am a little unclear again. Since I am looking for P(X≥36), wouldn't my equation be 1- (35.5 - μ)/σ.
 
  • #5
Shoney45 said:
Now I am a little unclear again. Since I am looking for P(X≥36), wouldn't my equation be 1- (35.5 - μ)/σ.

You want 1-P(Z>(35.5 - μ)/σ)

You'll need to calculate both μ and σ.

Remember when you were treating it as a binomial, X~Bin(n,p)

Now you are treating as an approximate normal X≈N(μ,σ2)

So for your binomial, what is E(X) and Var(X) ?
 
  • #6
rock.freak667 said:
You want 1-P(Z>(35.5 - μ)/σ)

You'll need to calculate both μ and σ.

Remember when you were treating it as a binomial, X~Bin(n,p)

Now you are treating as an approximate normal X≈N(μ,σ2)

So for your binomial, what is E(X) and Var(X) ?

So: μ = np = 180*1/6 = 30 and σ = [tex]\sqrt{}np(1-p)[/tex] = 180 * 1/6 * 5/6 = 25

So that the whole thing is 1 - (35.5-30)/25 = 4.5/25 = 1-0.18 = 1-0.5714 (from the table for standard normal curve areas) = 0.4286.

Am I tracking with this now?
 
  • #7
I'm also totally stumped on

2) What approximately, is the median of the number of the out of state students in a given dormitory?

What I'm guessing is that I have to set something equal to teh 50th percentile,a nd then use that to approximate the number of out of state students in a dormitory. I just can't figure out how to do it.
 
  • #8
Shoney45 said:
I'm also totally stumped on

2) What approximately, is the median of the number of the out of state students in a given dormitory?

What I'm guessing is that I have to set something equal to teh 50th percentile,a nd then use that to approximate the number of out of state students in a dormitory. I just can't figure out how to do it.

In a normal distribution, the mean = mode = median.
 
  • #9
Okay, so its that easy eh? So μ = np = 180*1/6 = 30 = median. Is that really it to find the median?
 
  • #10
That should be it I believe.
 
  • #11
rock.freak667 said:
That should be it I believe.

Thank you so much for your help on this one. I appreciate it a lot! I hope someone comes up to you on the street and gives you a large cloth sack, with a dollar sign on the side...stuffed full of sweaty money. Who knows? Ya might get lucky!
 

1. What is the normal distribution and why is it important in statistics?

The normal distribution, also known as the Gaussian distribution, is a probability distribution that is commonly used to model continuous data in statistics. It is important because it allows us to make predictions and draw conclusions about a population based on a sample, and it is the basis for many statistical tests and methods.

2. How is the normal distribution related to discrete populations?

The normal distribution is a continuous distribution, meaning that it can take on any value within a given range. In contrast, discrete populations have a finite number of values or categories. However, the normal distribution can still be used to approximate the behavior of discrete populations, especially if the sample size is large.

3. What are the characteristics of the normal distribution?

The normal distribution is bell-shaped, symmetric, and unimodal (has one peak). It is defined by its mean and standard deviation, with the majority of the data falling within 1, 2, or 3 standard deviations from the mean. It is also continuous and has a total area under the curve equal to 1.

4. How can we determine if a data set follows a normal distribution?

There are a few graphical and numerical methods for assessing normality, such as the histogram, QQ plot, and Shapiro-Wilk test. However, these methods are not definitive and should be used in conjunction with each other to make a conclusion about normality. It is also important to consider the context of the data and the sample size.

5. What are the uses of the normal distribution in real-world applications?

The normal distribution is used in a wide range of fields, including social sciences, natural sciences, and business. It is used to model various phenomena, such as heights and weights of individuals, test scores, and stock prices. It is also used in quality control, risk assessment, and in determining confidence intervals in statistical analyses.

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