Calculating Margin Of Error Formula
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For Dummies, 2nd Edition SPSS Statistics for Dummies, 3rd Edition Statistics II for Dummies Load more EducationMathStatisticsHow to Calculate the Margin calculating margin of error using confidence interval of Error for a Sample Proportion How to Calculate the Margin of Error for a Sample Proportion Related Book Statistics For Dummies, 2nd Edition By Deborah J. Rumsey When you report the results of a
Calculating Margin Of Error In A Survey
statistical survey, you need to include the margin of error. The general formula for the margin of error for a sample proportion (if certain conditions are met) is where is the sample proportion, n is the sample size, and z* is the appropriate z*-value for your desired level of confidence (from 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 margin of error calculation in excel 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. Hence 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 proportion: Find the sample size, n, and the sample proportion. The sample proportion is the number in the sample with the characteristic of interest, divided by n. Multiply the sample proportion by Divide the result by n. Take the square root of the calculated value. You now have the standard error, Multiply the result by the appropriate z*-value for the confidence level desired. Refer to the above table for the appropriate z*-value. If the confidence level is 95%, the z*-value is 1.96. Here's an example: Suppose that the Gallup Organization's latest poll sampled 1,000 people from the United States, and the results show that 520 people (52%) think the president is doing a good job, compared to 48% who don't think so. First, assume you want a 95% level of conf
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Margin Of Error Calculation Confidence Interval
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Margin Of Error Calculation Statistics
How to Calculate the Margin of Error for a Sample… Statistics Essentials For Dummies Statistics For Dummies, 2nd margin of error equation stats Edition SPSS Statistics for Dummies, 3rd Edition Statistics II for Dummies Load more EducationMathStatisticsHow to Calculate the Margin of Error for a Sample Proportion How to Calculate the http://www.dummies.com/education/math/statistics/how-to-calculate-the-margin-of-error-for-a-sample-proportion/ Margin of Error for a Sample Proportion Related Book Statistics For Dummies, 2nd Edition By Deborah J. Rumsey When you report the results of a statistical survey, you need to include the margin of error. The general formula for the margin of error for a sample proportion (if certain conditions are met) is where is the sample proportion, http://www.dummies.com/education/math/statistics/how-to-calculate-the-margin-of-error-for-a-sample-proportion/ n is the sample size, and z* is the appropriate z*-value for your desired level of confidence (from 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. Hence 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 proportion: Find the sample size, n, and the sample proportion. The sample proportion is the number in the sample with the characteristic of interest, divided by n. Multiply the sample proportion by Divide the result by n. Take the square root of the calculated value. You now have the standard error, Multiply the result by t
test AP formulas FAQ AP study guides AP calculators Binomial Chi-square f Dist Hypergeometric Multinomial Negative binomial Normal Poisson t Dist Random numbers Probability Bayes rule Combinations/permutations http://stattrek.com/estimation/margin-of-error.aspx Factorial Event counter Wizard Graphing Scientific Financial Calculator books AP calculator review http://www.had2know.com/business/compute-margin-of-error.html Statistics AP study guides Probability Survey sampling Excel Graphing calculators Book reviews Glossary AP practice exam Problems and solutions Formulas Notation Share with Friends Margin of Error In a confidence interval, the range of values above and below the sample statistic is called the margin of error. margin of For example, suppose we wanted to know the percentage of adults that exercise daily. We could devise a sample design to ensure that our sample estimate will not differ from the true population value by more than, say, 5 percent (the margin of error) 90 percent of the time (the confidence level). How to Compute the Margin of Error The margin margin of error of error can be defined by either of the following equations. Margin of error = Critical value x Standard deviation of the statistic Margin of error = Critical value x Standard error of the statistic If you know the standard deviation of the statistic, use the first equation to compute the margin of error. Otherwise, use the second equation. Previously, we described how to compute the standard deviation and standard error. How to Find the Critical Value The critical value is a factor used to compute the margin of error. This section describes how to find the critical value, when the sampling distribution of the statistic is normal or nearly normal. The central limit theorem states that the sampling distribution of a statistic will be nearly normal, if the sample size is large enough. As a rough guide, many statisticians say that a sample size of 30 is large enough when the population distribution is bell-shaped. But if the original population is badly skewed, has multiple peaks, and/or has outliers, researchers like the sample size to be even
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]