How To Find Margin Of Error Without Sample Size
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Margin Of Error Formula Proportion
join our mailing list for FREE content right to your inbox. margin of error definition Easy! Your email Submit RELATED ARTICLES How to Calculate the Margin of Error for a sampling error calculator Sample… Statistics Essentials For Dummies Statistics For Dummies, 2nd Edition SPSS Statistics for Dummies, 3rd Edition Statistics II for Dummies Load more EducationMathStatisticsHow to Calculate the http://stattrek.com/estimation/margin-of-error.aspx?Tutorial=AP Margin of Error for a Sample Mean How to Calculate the Margin of Error for a Sample Mean Related Book Statistics For Dummies, 2nd Edition By Deborah J. Rumsey When a research question asks you to find a statistical sample mean (or average), you need to report a margin of error, or MOE, http://www.dummies.com/education/math/statistics/how-to-calculate-the-margin-of-error-for-a-sample-mean/ for the sample mean. The general formula for the margin of error for the sample mean (assuming a certain condition is met -- see below) is is the population standard deviation, n is the sample size, and z* is the appropriate z*-value for your desired level of confidence (which you can find in the following table). z*-Values for Selected (Percentage) Confidence Levels Percentage Confidence z*-Value 80 1.28 90 1.645 95 1.96 98 2.33 99 2.58 Note that these values are taken from the standard normal (Z-) distribution. The area between each z* value and the negative of that z* value is the confidence percentage (approximately). For example, the area between z*=1.28 and z=-1.28 is approximately 0.80. This chart can be expanded to other confidence percentages as well. The chart shows only the confidence percentages most commonly used. Here are the steps for calculating the margin of error for a sample mean: Find the population sta
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to Compute the Margin of Error Margin of Error Calculator Enter the sample size n. Enter a value between 0 and 1 for p, or if p is unknown, use p = 0.5. Enter the population size N, or leave blank if the total population is large. npN In statistics, the margin of error represents the approximate amount of variance you can expect in polls and surveys. For example, suppose you conduct a poll that indicates 40% of people will vote 'no' on a proposition, and the margin of error is 3%. This means that if you were to conduct the same poll with another random sample of similar size, you could expect 37%-43% of the respondents in the second survey to also vote 'no.' The margin of error tells you how accurate poll results are; the smaller the margin of error, the greater the accuracy. There are two main formulas for calculating the margin of error, each explained below. In each formula, the sample size is denoted by n, the proportion of people responding a certain way is p, and the size of the total population is N. For some margin of error formulas, you do not need to know the value of N. 95% Confidence Interval Margin of Error If you have a sample that is drawn from a very large population (N is larger than 1,000,000), then you can compute the "95% confidence interval margin of error" with the formula MOE = (1.96)sqrt[p(1-p)/n]. If you perform 100 surveys with the same sample size drawn from the same poplulation, then 95% of the time you can expect the margin of error to fall within the bound above. As you can see, N does not factor into this equation for margin of error. If the total population is large enough, only the size of the random sample matters, not the total population. If the survey has multiple questions and there are several possible values for p, pick the value that is closest to 0.5. Here is an example: In a random survey of 1,000 Texans, 48% of the respondents liked chocolate ice cream more than vanilla, 46% liked vanilla more than chocolate, and 6% had no preference. First, set n = 1,000 and p = 0.48. Then (1.96)sqrt[(0.48)(0.52)/1000] = 0.03096, or 3.096%. This means that if you perform the same survey 100 more times, then 95% of the time the number of people who