cloud360 said:write it in terms of the mean (that u shaped thing in the normalization eqation), choose the correct value of Z for the confidence interval they give.
95% confidence interval ==> z=1.96 (for 2 tails)
98% confidence is something like , i don't know off by heart, check the normal table
lildrea88 said:i need a confidence interval for the uniform and bernoulli distribution...sorry i should have said that before
A confidence interval in a uniform distribution is a range of values that is likely to contain the true mean of the population with a certain level of confidence. It is a statistical measure that is used to estimate the unknown parameter of a population based on a sample from that population.
To find a confidence interval in a uniform distribution without using a formula, you can use a statistical software or an online calculator. These tools use the sample data to calculate the confidence interval and provide the results. Alternatively, you can manually calculate the confidence interval using the sample mean and standard deviation.
The confidence level in a uniform distribution represents the level of certainty or probability that the true mean of the population falls within the calculated confidence interval. It is usually expressed as a percentage, and a higher confidence level indicates a narrower interval and a more precise estimate of the population mean.
The width of a confidence interval in a uniform distribution can be affected by several factors, including 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 interval, while a higher confidence level will result in a wider interval.
The confidence level and confidence interval in a uniform distribution are inversely related. This means that as the confidence level increases, the confidence interval becomes wider, and as the confidence level decreases, the interval becomes narrower. This trade-off between precision and certainty is an important consideration when interpreting the results of a confidence interval.