How to find Confidence interval

In summary, the researcher surveyed 25 people and found that the average commute is 15 minutes with a standard deviation of 1.5 minutes. The 95% confidence interval on variance is 15.88 to 14.12. Based on this, it can be concluded that most people do not have a commute of 20 minutes. Chebyshev's inequality can be used to determine if at least 50% of people have a commute of 20 minutes or more.
  • #1
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A researcher surveys 25 people and finds that their average commute is 15 minutes with a standard deviation of 1.5 minutes. Calculate the 95 percent confidence interval on variance. Do most people have a commute of 20 minutes?

Confidence interval for variance? should I just use the variance instead of the standard deviation? so 1.5^2=2.25

root 25= 5

15+1.962.255 and 15−1.962.255
15+0.882 and 15−0.882

15.88,14.12

so, no , most people will not have a commute of 20 minutes

Is this right?

Thanks!
 
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  • #2
I don't follow your reasoning.

You need to clarify what you are testing ... identify the question the confidence interval is supposed to be used to answer.

It looks like you want to know if at least 50% of people have a commute of 20mins - based on your sample of 25 out of a large population.

You also want to figure what the confidence interval on variance has to do with figuring this out.
http://www.milefoot.com/math/stat/ci-variances.htm
 
  • #3
It's likely that nobody has a commute of exactly 20 minutes.

If you want to know if most people in the sample have a commute of 20 minutes or more, you could try using Chebyshev's inequality - i.e. by considering "the sample" to be the same as "the population".
 

Related to How to find Confidence interval

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 specified level of confidence. It is commonly used in statistical analysis to estimate the precision of a sample statistic.

2. How do I calculate a confidence interval?

To calculate a confidence interval, you need to know the sample mean, sample standard deviation, sample size, and the desired confidence level. The formula for a confidence interval is: sample mean ± (critical value x standard error), where the critical value is obtained from a z-table or t-table based on the confidence level and sample size.

3. What is the significance of the confidence level in a confidence interval?

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

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

A larger sample size will result in a narrower confidence interval because it reduces the standard error. This means that with a larger sample size, the estimate of the population parameter is more precise and therefore a narrower range of values is needed to capture it with a specified level of confidence.

5. Can a confidence interval be used to determine causation?

No, a confidence interval does not establish causation. It only provides a range of values that is likely to contain the true population parameter. In order to establish causation, other techniques such as experiments and observational studies are needed.

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