Moivre-Laplace theorem (homework)

In summary, the normal approximation to the success probability in 10 Bernoli trials is not accurate because 5<S(n)>9. However, the 1/2-correction can be used to improve the approximation.
  • #1
Poetria
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< Mentor Note -- thread moved to HH from the technical math forums, so no HH Template is shown >

I have no idea what I am doing wrong. Here is my problem:

S(n) - the number of successes in 10 Bernoulli trials, each with probability 0.7

I am supposed to use normal approximation to compute :

P{|S(n)/10-0.7|>0.2}

We are allowed to use a calculator.

I got:
|S(n)-7|>2|
5<S(n)>9

I have computed S*:

S(n)-7/1.44914
7=mean
1.44914- standard deviation

5*1.44914-7<Z<9*1.44914-7

Area (probability): 0.2451

But there is no such answer in the options.
 
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  • #2
Poetria said:
< Mentor Note -- thread moved to HH from the technical math forums, so no HH Template is shown >

I have no idea what I am doing wrong. Here is my problem:

S(n) - the number of successes in 10 Bernoulli trials, each with probability 0.7

I am supposed to use normal approximation to compute :

P{|S(n)/10-0.7|>0.2}

We are allowed to use a calculator.

I got:
|S(n)-7|>2|
5<S(n)>9

I have computed S*:

S(n)-7/1.44914
7=mean
1.44914- standard deviation

5*1.44914-7<Z<9*1.44914-7

Area (probability): 0.2451

But there is no such answer in the options.
What do you mean by 5<S(n)>9 ?

That's an invalid compound inequality.
 
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  • #3
I see. :( My line of thought was as follows:

S(n)-7>2 or S(n)-7<-2 (this is an absolute value equation: |S(n)/10-0.7|>0.2)

How to correct it?
 
  • #4
Poetria said:
I see. :( My line of thought was as follows:

S(n)-7>2 or S(n)-7<-2 (this is an absolute value equation: |S(n)/10-0.7|>0.2)

How to correct it?
What you have here is correct.

S(n)-7>2 or S(n)-7<-2

That says S(n) > 9 or S(n) < 5 . (You had S(n) > 5 )

You can't make these into a compound inequality.
 
  • #5
Poetria said:
< Mentor Note -- thread moved to HH from the technical math forums, so no HH Template is shown >

I have no idea what I am doing wrong. Here is my problem:

S(n) - the number of successes in 10 Bernoulli trials, each with probability 0.7

I am supposed to use normal approximation to compute :

P{|S(n)/10-0.7|>0.2}

We are allowed to use a calculator.

I got:
|S(n)-7|>2|
5<S(n)>9

I have computed S*:

S(n)-7/1.44914
********************
Wrong: use parentheses, like this: (S(n) - 7)/1.44914

********************

7=mean
1.44914- standard deviation

5*1.44914-7<Z<9*1.44914-7

***********************
Wrong: you need 5 > 7 + 1.44914*Z or 7 + 1.44914*Z > 9

The complement of the event "{S(n) < 5} or {S(n) > 9}" is {5 <= S(n) <= 9}, which translates to
5 <= 7 + 1.44914*Z <= 9, or -1.38 <= Z <= 1.38 in the normal approximation.

However, since n = 10 is small, the normal approximation might not be very good, but it can be improved a lot by using the so-called "1/2-correction". The random variable S(n) is discrete (taking values 0,1,2,...,10 only), so {5 < S(n) < 9} = {S(n) = 6,7,8}. In the normal approximation, replace this by {5.5 <= S_normal <= 8.5}, so
5.5 <= 7 + 1.44914*Z <= 8.5. The resulting increase in accuracy is striking in this example.

*********************

Area (probability): 0.2451

But there is no such answer in the options.
Poetria said:
< Mentor Note -- thread moved to HH from the technical math forums, so no HH Template is shown >

I have no idea what I am doing wrong. Here is my problem:

S(n) - the number of successes in 10 Bernoulli trials, each with probability 0.7

I am supposed to use normal approximation to compute :

P{|S(n)/10-0.7|>0.2}

We are allowed to use a calculator.

I got:
|S(n)-7|>2|
5<S(n)>9

I have computed S*:

S(n)-7/1.44914
7=mean
1.44914- standard deviation

5*1.44914-7<Z<9*1.44914-7

Area (probability): 0.2451

But there is no such answer in the options.
 
Last edited:
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  • #6
Thank you so much. I have tried to work it out. I think I got it. My problem is that I still can't get an exact answer. The closest (with the correction you have suggested):
if x = 5.5 I get 0.15031188 (I can choose 0.1675)
http://www.danielsoper.com/statcalc3/calc.aspx?id=53

The result: 0.08377348 is very imprecise.
Actually some calculators demand x, some Z. It is a mess.
 
  • #7
Sorry, I get 0.71860226. Even worse.
 
  • #8
I got it at last. :) Many thanks. :) You have helped me a lot. :) :) :)
 

FAQ: Moivre-Laplace theorem (homework)

What is the Moivre-Laplace theorem?

The Moivre-Laplace theorem, also known as the central limit theorem, is a fundamental theorem in probability theory that states that the sum of a large number of independent and identically distributed random variables will be approximately normally distributed.

What is the importance of the Moivre-Laplace theorem?

The Moivre-Laplace theorem is important because it allows us to make predictions about the behavior of complex systems by simplifying them into a single, normally distributed variable. It also serves as the foundation for many statistical methods and models.

What are the assumptions of the Moivre-Laplace theorem?

The Moivre-Laplace theorem assumes that the random variables are independent and identically distributed, the sample size is large, and the probability of success for each variable is not too small or too large. It also assumes that the variables are not correlated and that the distribution is not skewed.

How is the Moivre-Laplace theorem used in real-world applications?

The Moivre-Laplace theorem is used in a variety of fields, such as finance, economics, and social sciences, to make predictions and analyze data. For example, it is used in hypothesis testing, confidence intervals, and regression analysis.

How is the Moivre-Laplace theorem related to the normal distribution?

The Moivre-Laplace theorem states that the sum of a large number of independent and identically distributed random variables will be approximately normally distributed. Therefore, it is closely related to the normal distribution, which is a commonly used probability distribution in statistics.

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