Define Margin Of Error In Statistics
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engineering, see Tolerance (engineering). For the eponymous movie, see Margin for error (film). The top portion charts probability density against actual percentage, showing the relative probability that the actual percentage is realised, based on the sampled percentage. In the probability margin of error bottom portion, each line segment shows the 95% confidence interval of a sampling (with the 3 margin of error margin of error on the left, and unbiased samples on the right). Note the greater the unbiased samples, the smaller the margin define margin of error ap gov of error. The margin of error is a statistic expressing the amount of random sampling error in a survey's results. It asserts a likelihood (not a certainty) that the result from a sample is close to the http://stattrek.com/statistics/dictionary.aspx?definition=Margin%20of%20error number one would get if the whole population had been queried. The likelihood of a result being "within the margin of error" is itself a probability, commonly 95%, though other values are sometimes used. The larger the margin of error, the less confidence one should have that the poll's reported results are close to the true figures; that is, the figures for the whole population. Margin of error applies whenever a population is incompletely https://en.wikipedia.org/wiki/Margin_of_error sampled. Margin of error is often used in non-survey contexts to indicate observational error in reporting measured quantities. In astronomy, for example, the convention is to report the margin of error as, for example, 4.2421(16) light-years (the distance to Proxima Centauri), with the number in parentheses indicating the expected range of values in the matching digits preceding; in this case, 4.2421(16) is equivalent to 4.2421 ± 0.0016.[1] The latter notation, with the "±", is more commonly seen in most other science and engineering fields. Contents 1 Explanation 2 Concept 2.1 Basic concept 2.2 Calculations assuming random sampling 2.3 Definition 2.4 Different confidence levels 2.5 Maximum and specific margins of error 2.6 Effect of population size 2.7 Other statistics 3 Comparing percentages 4 See also 5 Notes 6 References 7 External links Explanation[edit] The margin of error is usually defined as the "radius" (or half the width) of a confidence interval for a particular statistic from a survey. One example is the percent of people who prefer product A versus product B. When a single, global margin of error is reported for a survey, it refers to the maximum margin of error for all reported percentages using the full sample from the survey. If the statistic is a percentage, this maximum margin of error can be calculated as the radius
Tour Start here for a quick overview of the site Help Center Detailed answers to any questions you might have Meta Discuss the workings and policies of this site About Us Learn more about Stack Overflow the company Business Learn more about hiring developers http://stats.stackexchange.com/questions/22021/how-are-margins-of-error-related-to-confidence-intervals or posting ads with us Cross Validated Questions Tags Users Badges Unanswered Ask Question _ Cross Validated is a question and answer site for people interested in statistics, machine learning, data analysis, data mining, and data visualization. Join them; it only http://www.robertniles.com/stats/margin.shtml takes a minute: Sign up Here's how it works: Anybody can ask a question Anybody can answer The best answers are voted up and rise to the top How are margins of error related to confidence Intervals? up vote 8 margin of down vote favorite 2 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"? confidence-interval survey polling share|improve this question edited Jan 31 '12 at 19:31 whuber♦ 145k17281540 asked Jan 31 '12 at 15:56 Mintuz 143115 1 Useful discussions on this topic can be found by searching our margin of error site. –whuber♦ Jan 31 '12 at 19:30 add a comment| 2 Answers 2 active oldest votes up vote 9 down vote accepted The Internet is full of garbage, as all of us know. It helps to find authoritative sources and focus on them to help resolve such issues. A pamphlet published by the American Statistical Association (attributed to Fritz Scheuren and "thoroughly updated circa 1997") defines the margin of error as a 95% confidence interval (p. 64, at right). In light of this, it is surprising that the Wikipedia article on margin of error uses a different definition, even though it references this pamphlet! Wikipedia writes, The margin of error is usually defined as the "radius" (or half the width) of a confidence interval for a particular statistic from a survey. ... When a single, global margin of error is reported for a survey, it refers to the maximum margin of error for all reported percentages using the full sample from the survey. In other words, to Wikipedia the MoE is one-half the maximum width of a set of confidence intervals (which might have coverages differing from 95%). We have discussed this confusion (or, at least, lack of standardization) in comments elsewhere on this site. Our conclusion was that you need to be clear what you mean by "margin of error" whenever you use that term. share|improve this answer edited Jan 31 '12 at 19:38 answered Jan 31 '12 at 19:21 whuber&
accurate, assuming you counted the votes correctly. (By the way, there's a whole other topic in math that describes the errors people can make when they try to measure things like that. But, for now, let's assume you can count with 100% accuracy.) Here's the problem: Running elections costs a lot of money. It's simply not practical to conduct a public election every time you want to test a new product or ad campaign. So companies, campaigns and news organizations ask a randomly selected small number of people instead. The idea is that you're surveying a sample of people who will accurately represent the beliefs or opinions of the entire population. But how many people do you need to ask to get a representative sample? The best way to figure this one is to think about it backwards. Let's say you picked a specific number of people in the United States at random. What then is the chance that the people you picked do not accurately represent the U.S. population as a whole? For example, what is the chance that the percentage of those people you picked who said their favorite color was blue does not match the percentage of people in the entire U.S. who like blue best? Of course, our little mental exercise here assumes you didn't do anything sneaky like phrase your question in a way to make people more or less likely to pick blue as their favorite color. Like, say, telling people "You know, the color blue has been linked to cancer. Now that I've told you that, what is your favorite color?" That's called a leading question, and it's a big no-no in surveying. Common sense will tell you (if you listen...) that the chance that your sample is off the mark will decrease as you add more people to your sample. In other words, the more people you ask, the more likely you are to get a representative sample. This i