Help finding Confidence Intervals

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In summary, the problem involves calculating a confidence interval for the number of coins in a jar with a known probability distribution. The problem also suggests using a normal approximation to the appropriate distribution and defines q as the number of quarters and N as the total number of coins in the population. The optimal change is always given, but it is unclear how this relates to the problem. It is recommended to post this in the homework section for assistance.
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rcode
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The problem states: I have 150 quarters. Calculate a confidence interval for the number of coins in my jar. The optimal change is always given. The distribution of coins are discrete uniform.

I have also found that probability of a quarter=.31, probability of a penny=.42, probability of a nickel=.08, and probability of a dime=.1702.

Guidlines suggest to say that q=# of quarters as random variable which comes from population of N=total number of coins as parameter. Use a normal approximation to the appropriate distribution.

Thanks for any help, I'm so stuck
 
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  • #2
I don't understand your problem. You randomly fill a jar with coins (with known probability distribution) until you have 150 quarters in?
The optimal change is always given. The distribution of coins are discrete uniform.
How does this fit to the remaining problem statement?

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Related to Help finding Confidence Intervals

1. What is a confidence interval?

A confidence interval is a range of values that is likely to contain the true population parameter with a certain degree of confidence. It is used to estimate the true value of a population parameter based on a sample of data.

2. How is a confidence interval calculated?

A confidence interval is calculated by taking the sample mean and adding or subtracting the margin of error. The margin of error is determined by the sample size, the standard deviation of the sample, and the desired level of confidence.

3. What does the level of confidence represent in a confidence interval?

The level of confidence represents the probability that the true population parameter falls within the calculated confidence interval. For example, a 95% confidence interval means that there is a 95% chance that the true population parameter falls within the calculated range.

4. How does sample size affect the width of a confidence interval?

The larger the sample size, the narrower the confidence interval will be. This is because a larger sample size reduces the margin of error and increases the precision of the estimate.

5. When is it appropriate to use a confidence interval?

A confidence interval is commonly used in inferential statistics to estimate the true value of a population parameter based on a sample of data. It is particularly useful when the population standard deviation is unknown or when conducting hypothesis testing.

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