Confidence Level for Proportion

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In summary, the conversation discusses the production of axle shafts and the testing process to determine the proportion of shafts with a rough surface. In part A, the quality control department has sampled 150 shafts and found that between 15% and 25% are outside the industry standards. The confidence level associated with this estimate is calculated to be 89%. In part B, the question is unclear, but it may be asking for the sample size needed to estimate the proportion of shafts outside the standards with a 95% probability and an accuracy of ±3 percentage points.
  • #1
masterchiefo
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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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  • #2
anyone can help me :(
 
  • #3
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.
 

FAQ: Confidence Level for Proportion

1. What is a confidence level for proportion?

A confidence level for proportion is a statistical term that refers to the level of certainty or confidence that a population proportion falls within a certain range. It is usually expressed as a percentage, such as 95% or 99%, and represents the likelihood that the true population proportion falls within a specified interval.

2. How is confidence level for proportion calculated?

The confidence level for proportion is calculated using a formula that takes into account the sample size, the sample proportion, and the standard error. The most common formula is the Wald method, which uses the normal distribution to estimate the confidence interval. Other methods include the Wilson score interval and the Agresti-Coull interval.

3. Why is confidence level for proportion important?

Confidence level for proportion is important because it helps us understand the precision of our estimates. By calculating a confidence interval, we can determine the range within which the true population proportion is likely to fall. This is particularly useful in scientific research, where we want to make accurate and reliable conclusions about a population based on a sample.

4. How is confidence level for proportion related to margin of error?

Confidence level for proportion and margin of error are closely related. A higher confidence level means a larger margin of error, and vice versa. This is because a higher confidence level requires a wider interval to capture the true population proportion, while a lower confidence level can have a narrower interval. However, it's important to note that the margin of error also depends on the sample size and the variability of the data.

5. What factors can affect the confidence level for proportion?

Several factors can affect the confidence level for proportion, including the sample size, the variability of the data, and the chosen confidence interval. A larger sample size generally leads to a higher confidence level, while a smaller sample size can result in a lower confidence level. Additionally, if the data is highly variable, the confidence interval may be wider, resulting in a lower confidence level.

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