From what I can understand, the difference is a technical one: the average person might equate one with the other.
A confidence interval is defined to be an interval where you are x% sure that your true value lies.
So if I estimated your weight was... 250 lbs (~113 kg or ~18 stone) but said that my confidence interval was 99% for the range of 50 lbs - 500 lbs, that could be true (but worthless).
You can see how problems could arise: the larger the interval (range of values), the higher confidence I can have that the true answer is somewhere in there.
But the larger my range of values, the less accurate it is as a whole - as in my earlier example, if I estimated your weight to be between 50 - 500 lbs, it would be technically correct, but useless if we were trying to figure out how many people we were trying to fit on say, the last helicopter out of Saigon.
A margin of error, statistically speaking, (MoE) is simply defined (as far as I can tell) as a confidence interval of 95%.
Notes:
A margin of error shrinks as the sample size grows. A good way of estimating a margin of error is the expression (0.98)/(sqrt(n)), where n is the size of the sample in question.
You may note that many polls in the news have a margin of error of 3.1% - this is due to the fact that many polls use 1,000 people for a nice 'round' number.
A margin of error is unavoidable and ONLY REFLECTS THE SIZE OF THE SAMPLE.
It does not, I repeat, not indicate any mistakes in the way the survey is carried out. A sample of 2,000,000 Adolf Hitlers would have a MoE of only 0.06% but might indicate that the continent of Europe believes in the therapeutic power of racial cleansing.
Final note:
Different people may use the term 'margin of error' slightly differently. Clarify, clarify, clarify!
The width of the confidence interval willdecrease if you decrease the confidence level,increase if you decrease the sample sizeincrease if you decrease the margin of error.
The confidence interval consists of a central value and a margin of error around that value. If it is an X% confidence interval then there is a X% probability that the true value of the statistic in question lies inside the interval. Another way of looking at it is that if you took repeated samples and calculated the test statistic each time, you should expect X% of the test statistics to fall within the confidence interval.
Confidence IntervalsConfidence interval (CI) is a parameter with a degree of confidence. Thus, 95 % CI means parameter with 95 % of confidence level. The most commonly used is 95 % confidence interval.Confidence intervals for means and proportions are calculated as follows:point estimate ± margin of error.
It depends on whether it is the Type I Error or the Type II Error that is increased.
1.0966
Generally speaking an x% confidence interval has a margin of error of (100-x)%.
No. The width of the confidence interval depends on the confidence level. The width of the confidence interval increases as the degree of confidence demanded from the statistical test increases.
The width of the confidence interval willdecrease if you decrease the confidence level,increase if you decrease the sample sizeincrease if you decrease the margin of error.
The standard deviation is used in the numerator of the margin of error calculation. As the standard deviation increases, the margin of error increases; therefore the confidence interval width increases. So, the confidence interval gets wider.
The confidence interval consists of a central value and a margin of error around that value. If it is an X% confidence interval then there is a X% probability that the true value of the statistic in question lies inside the interval. Another way of looking at it is that if you took repeated samples and calculated the test statistic each time, you should expect X% of the test statistics to fall within the confidence interval.
It would be the difference between the two darker lines, or index lines, and then divide the space in between with your difference.
The formula for margin of error is (Z*)*(Standard Deviation))/(sqrt(N)), so as N increases, the margin of error decreases. Here N went from 100 to 5000, so N has increased by 4900. This means the margin of error decreases. Since the confidence interval is the mean plus or minus the margin of error, a smaller margin of error means that the confidence interval is narrower.
if the confidence interval is 24.4 to 38.0 than the average is the exact middle: 31.2, and the margin of error is 6.8
Confidence IntervalsConfidence interval (CI) is a parameter with a degree of confidence. Thus, 95 % CI means parameter with 95 % of confidence level. The most commonly used is 95 % confidence interval.Confidence intervals for means and proportions are calculated as follows:point estimate ± margin of error.
The confidence interval radius determines the margin of error. If you want more information visit: http://en.wikipedia.org/wiki/Margin_of_error
It depends on whether it is the Type I Error or the Type II Error that is increased.
1.0966