Probability of a Confidence Interval

In summary, the probability that a confidence interval with alpha=10% will have at least 85 of 100 predicted means within the calculated range is approximately 96%. This assumes a normal distribution and the Central Limit Theorem, with the experiment being conducted only once.
  • #1
shalomhk
2
0
What's the probability that a confidence interval (with alpha=10%), will have at least 85 of 100 predicted means within the calculated interval range (xbar +/- 1.645(sigma/sqrt(n)))?

I understand that on average 90% of my means will be located in this range (and I know how to find this range), but the figure 90% is an AVERAGE.

Suppose I do this experiment ONCE, and only once. What's the probability that at least (>=) 85 (of the 100, or 85%) of the mean values will be within this range?

Assumptions: Normal (by Central Limit Theorem as n=100 is greater than 30)


Thanks!
 
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  • #2
sum(n=85,100,.9^n*.1^(100-n)*binomial(100,n)) ≈ 96% of the time.
 
  • #3
Thanks!
 

What is a confidence interval?

A confidence interval is a range of values that is likely to include the true population parameter with a certain level of confidence. It is often used in inferential statistics to estimate the true value of a population parameter based on a sample.

Why is it important to calculate the probability of a confidence interval?

The probability of a confidence interval helps us understand the likelihood that the true population parameter falls within the calculated interval. This allows us to make more informed decisions and draw more accurate conclusions based on our sample data.

How is the probability of a confidence interval calculated?

The probability of a confidence interval is calculated using the confidence level, sample size, and standard deviation of the sample. It is typically calculated using a formula or using statistical software.

What factors can affect the probability of a confidence interval?

The probability of a confidence interval can be affected by the confidence level, sample size, and standard deviation of the sample. A higher confidence level will result in a wider interval and a lower probability, while a larger sample size and smaller standard deviation will result in a narrower interval and a higher probability.

How can the probability of a confidence interval be used in decision making?

The probability of a confidence interval can be used to evaluate the precision of our estimates and determine the level of confidence we have in our results. It can also be used to compare different groups or treatments and determine if there is a statistically significant difference between them.

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