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Can somebody tell me the difference between margins of error and confidence intervals? On the Internet I see these two meanings getting used interchangeably. … Is it right to say, "Confidence intervals are shown as 1.96 and displayed on the graphs as error margins"? …

I used an online calculator that shows that the margin of error is 4% population size: 1000,000 confidence level (%): 95 Your sample size: 498 The margin of error is 4% (online calculator) Manual Calculation … , sx̄ = s / √N = 36/ √10 =11.39863539591 Margin of Error = critical value x Standard Error = 1.96 x 11.39863539591 = 22.341 Please advise why the margin of error (using manual calculation) results in …

The objective is to sample that binomial distribution, and estimate $p$ and find the confidence interval such that $p \in \hat{p} \pm \epsilon$, were $\hat{p}$ is the sample mean and $\epsilon$ the margin … Q1: Why do they compute two margin errors $\epsilon$ and $\epsilon_{r}$. I understand that only $\epsilon_{r}$, the margin error that is computed with the number of polling places, is correct. …

My understanding is that 1000 responses is more than enough for a margin of error of 3% or so with a confidence level of 95%. OK, so far so good. … Is it correct to report that 55% of women prefer vanilla with a 3% margin of error and confidence of 95%? …

Wikipedia's Margin of Error entry says that a random sample of size 400 will give a margin of error, at a 95% confidence level, of 0.98/20 or 0.049 - just under 5% given an infinite population … , the resulting proportion would be accurate with a 95% confidence level, to a margin of error below 5%. …

But the margin of error is 3%). Trying to understand how this "margin of error" is calculated I searched the internet and came across this article. … Using a level of confidence of 95%, they can determine that the margin of error is 2%. Anything between 65% and 69% (67% +/- 2) accurately describes the entire customer database. …

From there he extrapolates that: But if polls are missing election outcomes by 5 or 6 points on average, that means the margin of error (or 95 percent confidence interval) is very large indeed. … Specifically, a 6-point average error in forecasting the final margin translates to a true margin of error of plus or minus 13 to 15 percentage points, depending on how you calculate it. …

343.45, 352.35, 351.95, 289.90, 331.75, 336.75, 341.65, 356.75, 330.95, 360.25, 297.25, 348.95, 324.50, 338.90, 331.60, 333.80) I want to do an estimation of the mean by establishing a margin … of error and a confidence interval, using a 95% confidence-level. …

Background: We want to find the margin of error, at a 95% confidence interval on a particular question in a survey. If there are 10 questions in the survey, this question is towards the very end. … How will I then calculate the margin of error? …

The survey has an overall reported margin of error of +/- 4% at the 95% confidence interval and I understand that this was derived from a table based on the CI and the number of respondents. … My problem is that after reading about margin of error it seems incorrect to have calculated a margin for the entire survey. …

The equation from the article shows that the margin of error for 95% confidence (Z=2) is 0.1. … It seems like my actual margin of error for 95% confidence is around .03, since .97^100 = .048. So... what gives? Are the formulas in the article only useful when the probability is near .5? …

Only through simulation was I able to verify it does so empirically (here I set $\sigma = 0.15$): I'd really like to be able to show something like, "for N > 1000, the margin of error for $S^2$ is ___ … ", but I don't see how margin of error is easily extracted for the sample variance, as it is for sample mean, and I'm not sure how to show the decrease in interval length analytically. …

My question is, how many samples do i need to train on for a given ad to have confidence in its prediction? Is there a way to compute the margin of error? … My idea is that, I can define a margin of error (say 1% of sample mean) and see if the given sample size gives me a margin of error less than this threshold. …

We're now putting the report together and want to include margin of error in our statistics. … The user-fillable boxes asked me for sample size + population size and the confidence interval I wished to calculate at (95%), and returned a 1% margin of error. …

Exactly how do I solve the margin of error when all the other variables (sample size, confidence level, distribution and population*) are known? …