What is the confidence interval for a 100 ohm resistor with 10% tolerance?

In summary, a confidence interval is a range of values that is likely to contain the true population parameter with a certain level of confidence. It is calculated using the sample mean, standard error, and margin of error. The confidence level represents the probability that the true population parameter falls within the interval. The width of a confidence interval depends on sample size, data variability, and confidence level. In scientific research, confidence intervals are important for making accurate conclusions and comparing results between studies.
  • #1
vptran84
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What is the 95% confidence interval for 100 ohm resister with 10% tolerence?

Here is my work so far, can someone please tell me if I am doing it wrong or right? Thank you in advance.

from table 95%: k = 1.96
100 * 0.1( which is the 10% tolerance) = 10

10 / sigma >= 1.96
Sigma <= 5.10204

confidence interval limits:
100ohm +- 1.96(5.10204ohms) = 100ohm +- 10ohms
 
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  • #2
Maybe my definition of tolerance is wrong, but isn't 1 sigma = 10% * 100ohms = 10 ohms?

A 95% confidence interval would then be +/- 1.96 sigma.
 
  • #3


Your work looks correct so far. To find the 95% confidence interval, we can use the formula:

95% CI = mean +/- margin of error

The mean in this case is 100 ohms, and the margin of error is 10 ohms (calculated from the tolerance of 10%). Therefore, the 95% confidence interval for a 100 ohm resistor with 10% tolerance would be:

95% CI = 100 ohms +/- 10 ohms

This means that we can be 95% confident that the true resistance of the resistor falls within the range of 90 ohms to 110 ohms.
 

FAQ: What is the confidence interval for a 100 ohm resistor with 10% tolerance?

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 level of confidence. It is used to estimate the true value of a population based on a sample.

How is a confidence interval calculated?

A confidence interval is calculated using the sample mean and standard error. The standard error is calculated as the standard deviation of the sample divided by the square root of the sample size. The confidence interval is then calculated by adding and subtracting the margin of error from the sample mean.

What does the confidence level represent?

The confidence level represents the level of certainty or probability that the true population parameter falls within the calculated confidence interval. For example, a confidence level of 95% means that we are 95% confident that the true population parameter falls within the calculated interval.

What factors affect the width of a confidence interval?

The width of a confidence interval depends on the sample size, the variability of the data, and the chosen confidence level. A larger sample size and lower variability will result in a narrower confidence interval, while a higher confidence level will result in a wider interval.

Why are confidence intervals important in scientific research?

Confidence intervals are important in scientific research because they provide a range of values that is likely to contain the true population parameter. This allows us to make more accurate and reliable conclusions about the population based on our sample. Additionally, confidence intervals can help us compare the results of different studies and determine if they are statistically significant or not.

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