98 Error Margin
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Margin Of Sampling Error Formula
Margin of Error (video) What is a Margin of Error? The margin of error is the range of values below and above the sample statistic in a confidence interval. The confidence interval is a way to show what the uncertainty is with a certain statistic (i.e. from a poll or survey). For example, a poll might state that there is a 98% confidence interval of 4.88 and 5.26. That means if the poll is repeated using the how to figure margin of error same techniques, 98% of the time the true population parameter (parameter vs. statistic) will fall within the interval estimates (i.e. 4.88 and 5.26) 98% of the time. What is a Margin of Error Percentage? A margin of error tells you how many percentage points your results will differ from the real population value. For example, a 95% confidence interval with a 4 percent margin of error means that your statistic will be within 4 percentage points of the real population value 95% of the time. The Margin of Error can be calculated in two ways: Margin of error = Critical value x Standard deviation Margin of error = Critical value x Standard error of the statistic Statistics Aren't Always Right! The idea behind confidence levels and margins of error is that any survey or poll will differ from the true population by a certain amount. However, confidence intervals and margins of error reflect the fact that there is room for error, so although 95% or 98% confidence with a 2 percent Margin of Error might sound like a very good statistic, room for error is built in, which means sometimes statistics are wrong. For example, a Gallup poll in 2012 (incorrectly) stated that Romney would win the 2012 election with Romney at 49% and Obama at 48%. The stated confidence level was 95% with a margin of er
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Margin Of Error Calculator 98
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Error Margin Definition
math at any level and professionals in related fields. Join them; it only takes a minute: Sign up Here's how it works: Anybody can ask a question Anybody can answer The best answers are voted http://www.statisticshowto.com/how-to-calculate-margin-of-error/ up and rise to the top Margin of error and $98\%$ confidence interval question for stats people :) up vote 3 down vote favorite The question is (this is homework, for an online class, no teacher so at times confusing) Carl conducted an experiment to determine if there is a difference in mean body temperature between men and women. He found that the mean body temperature for men in sample http://math.stackexchange.com/questions/547194/margin-of-error-and-98-confidence-interval-question-for-stats-people was $91.1$ with a population standard deviation of $.52$ and mean body temperature for women in sample was $97.6$ with population standard deviation of $.45$. -Assuming population of body temperatures for men and women were normally distributed, calculate the $98\%$ confidence interval and the margin of error for both. *I have a bit of experience with confidence interval, but only have $90\%, 95\%,$ and $99\%$ and the course gave me a "confidence interval calculator" and has only that. Also, I have never before heard of margin of error, when I looked it up I didn't understand it. Could someone please explain to me in a way that I would easily be able to understand? (I asked the same question yesterday, but no one replied. I hope someone can respond today, I wasn't sure I could refresh the old one" Thank you. statistics share|cite|improve this question edited May 31 '14 at 1:20 Cookie 7,961112559 asked Oct 31 '13 at 18:06 shari 2114 We need sample sizes to do this. –Michael Hardy Oct 31 '13 at 18:10 Thats what I thought, They never gave me a sample size. Is that something I can find? –shari Oct 31 '13 at 18:11 It can't be f
Software To Calculate Confidence Intervals Print Lesson Confidence Intervals Constructing confidence intervals to estimate a population proportion NOTE: the following interval calculations for the proportion confidence interval is dependent on the following assumptions being satisfied: np ≥ 10 and n(1-p) ≥ 10. If p http://stat.psu.edu/~ajw13/stat200_upd/07_CI/03_CI_CI.htm is unknown then use the sample proportion. The goal is to estimate p = proportion with http://americanresearchgroup.com/moe.html a particular trait or opinion in a population. Sample statistic = (read "p-hat") = proportion of observed sample with the trait or opinion we’re studying. Standard error of , where n = sample size. Multiplier comes from this table Confidence Level Multiplier .90 (90%) 1.645 or 1.65 .95 (95%) 1.96, usually rounded to 2 .98 (98%) 2.33 .99 (99%) 2.58 The value of margin of the multiplier increases as the confidence level increases. This leads to wider intervals for higher confidence levels. We are more confident of catching the population value when we use a wider interval. Example In the year 2001 Youth Risk Behavior survey done by the U.S. Centers for Disease Control, 747 out of n = 1168 female 12th graders said the always use a seatbelt when driving. Goal: Estimate proportion always using seatbelt when driving in the population of all margin of error U.S. 12th grade female drivers. Check assumption: (1168)*(0.64) = 747 and (1168)*(0.36) = 421 both of which are at least 10. Sample statistic is = = 747 / 1168 = .64 Standard error = A 95% confidence interval estimate is .64 ± 2 (.014), which is .612 to .668 With 95% confidence, we estimate that between .612 (61.2%) and .668 (66.8%) of all 12th grade female drivers always wear their seatbelt when driving. Example Continued: For the seatbelt wearing example, a 99% confidence interval for the population proportion is .64 ± 2.58 (.014), which is .64 ± .036, or .604 to .676. With 99% confidence, we estimate that between .604 (60.4%) and .676 (67.6%) of all 12th grade female drivers always wear their seatbelt when driving. Notice that the 99% confidence interval is slightly wider than the 95% confidence interval. IN the same situation, the greater the confidence level, the wider the interval. Notice also, that the only the value of the multiplier differed in the calculations of the 95% and 98% intervals. Using Confidence Intervals to Compare Groups A somewhat informal method for comparing two or more populations is to compare confidence intervals for the value of a parameter. If the confidence intervals do not overlap, it is reasonable to conclude that the parameter value differs for the two populations. Example In the Youth Risk Behavior survey, 677 out of n = 1356 12th
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