Confidence Level for Proportion

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The discussion revolves around calculating the confidence level for the proportion of axle shafts with surface defects and determining the necessary sample size for a more precise estimate. In part A, the quality control department found that 15% to 25% of a sample of 150 axle shafts were defective, leading to a calculated confidence level of 89%. For part B, the company aims to estimate the defect rate within 3% accuracy at a 95% confidence level, but there is confusion regarding the interpretation of the required sample size. The calculations suggest that an additional 1220 axle shafts would be needed to meet this accuracy requirement. Clarification is sought on whether the question pertains to estimating the defect percentage or achieving a specific error margin.
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Homework Statement


[/B]
A company produces batches of 1800 axle shafts . These are tested to determine the proportion of those with too rough surface according to the standards set in the industry.

A) The quality control department of a sample of 150 axle shafts in a lot and concluded that there are between 15 % and 25 % of the axle shafts in this set that are outside the norms . Calculate the confidence level associated with this estimate.

B) The Company would estimate at 3.0 % near the proportion of axle shafts located outside the standards , 19 times out of 20. How many additional axle shafts should you consider it ? You must take into account the results obtained in A) .

Homework Equations


(ME)/(sqrt((P*(1-P))/n)*sqrt(1-(n/N)) = Zalpha/2
normcdf(-Zalpha/2,Zalpha/2)

The Attempt at a Solution


A)[/B]
Known variable:
N = 1800
n=150
[15%,25%] ---> P= (15+25)/2 =20% or 0.20
ME = (25-15)/2 = 5% or 0.05

(ME)/(sqrt((P*(1-P))/n)*sqrt(1-(n/N)) = Zalpha/2
(0.05)/(sqrt((0.2*(1-0.2))/n)*sqrt(1-(150/1800)) = Zalpha/2
Zalpha/2 = 1.59901

normcdf(-Zalpha/2,Zalpha/2)
normcdf(-1.59901,1.59901) = 0.89 or 89%

This is correct answer for A) checked in book.Now for part B)
ME = 3% = 0.03
19 times out of 20= 95% = 1-alpha

[p+invnorm(0.025)*(sqrt((P*(1-P))/n)*sqrt(1-(n/N)) , p+invnorm(1-0.025)*(sqrt((P*(1-P))/n)*sqrt(1-(n/N))]
[0.2+invnorm(0.025)*(sqrt((0.5*(1-0.5))/150)*sqrt(1-(150/1900)) , 0.2+invnorm(1-0.025)*(sqrt((0.5*(1-0.5))/150)*sqrt(1-(150/1800))]

[0.1233,0.2766]solve(invnorm(1-0.025)*(sqrt((0.2766*(1-0.2766))/n)*sqrt(1-(n/1800))=0.03) for n
n = 579.225

1800-580 = 1220 addition needs.

I am doing something wrong for the part B).
Please point me to the right direction, maybe my P that I have is not correct.
 
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masterchiefo said:

Homework Statement


[/B]
A company produces batches of 1800 axle shafts . These are tested to determine the proportion of those with too rough surface according to the standards set in the industry.

A) The quality control department of a sample of 150 axle shafts in a lot and concluded that there are between 15 % and 25 % of the axle shafts in this set that are outside the norms . Calculate the confidence level associated with this estimate.

B) The Company would estimate at 3.0 % near the proportion of axle shafts located outside the standards , 19 times out of 20. How many additional axle shafts should you consider it ? You must take into account the results obtained in A) .

Homework Equations


(ME)/(sqrt((P*(1-P))/n)*sqrt(1-(n/N)) = Zalpha/2
normcdf(-Zalpha/2,Zalpha/2)

The Attempt at a Solution


A)[/B]
Known variable:
N = 1800
n=150
[15%,25%] ---> P= (15+25)/2 =20% or 0.20
ME = (25-15)/2 = 5% or 0.05

(ME)/(sqrt((P*(1-P))/n)*sqrt(1-(n/N)) = Zalpha/2
(0.05)/(sqrt((0.2*(1-0.2))/n)*sqrt(1-(150/1800)) = Zalpha/2
Zalpha/2 = 1.59901

normcdf(-Zalpha/2,Zalpha/2)
normcdf(-1.59901,1.59901) = 0.89 or 89%

This is correct answer for A) checked in book.Now for part B)
ME = 3% = 0.03
19 times out of 20= 95% = 1-alpha

[p+invnorm(0.025)*(sqrt((P*(1-P))/n)*sqrt(1-(n/N)) , p+invnorm(1-0.025)*(sqrt((P*(1-P))/n)*sqrt(1-(n/N))]
[0.2+invnorm(0.025)*(sqrt((0.5*(1-0.5))/150)*sqrt(1-(150/1900)) , 0.2+invnorm(1-0.025)*(sqrt((0.5*(1-0.5))/150)*sqrt(1-(150/1800))]

[0.1233,0.2766]solve(invnorm(1-0.025)*(sqrt((0.2766*(1-0.2766))/n)*sqrt(1-(n/1800))=0.03) for n
n = 579.225

1800-580 = 1220 addition needs.

I am doing something wrong for the part B).
Please point me to the right direction, maybe my P that I have is not correct.

I cannot understand what part B is is asking, because I cannot understand what it is saying. Are you asking for the sample size that would allow the firm to estimate (with probability >= 95%) the percentage of items outside the standard to an accuracy of within ± 3 percentage points--that is, an interval (p - 3/100, p + 3/100)--or are you asking for an estimate accurate to within a 3% error--that is, an interval (0.97*p, 1.03*p)? These are two very different concepts.
 
First, I tried to show that ##f_n## converges uniformly on ##[0,2\pi]##, which is true since ##f_n \rightarrow 0## for ##n \rightarrow \infty## and ##\sigma_n=\mathrm{sup}\left| \frac{\sin\left(\frac{n^2}{n+\frac 15}x\right)}{n^{x^2-3x+3}} \right| \leq \frac{1}{|n^{x^2-3x+3}|} \leq \frac{1}{n^{\frac 34}}\rightarrow 0##. I can't use neither Leibnitz's test nor Abel's test. For Dirichlet's test I would need to show, that ##\sin\left(\frac{n^2}{n+\frac 15}x \right)## has partialy bounded sums...

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