Compute Standard Error Observed Proportion
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0 otherwise. The standard deviation of any variable involves the
Standard Deviation Of P Hat
expression . Let's suppose there are m 1s (and n-m 0s) among the n subjects. Then, and is equal to (1-m/n) for m observations and 0-m/n p hat formula for (n-m) observations. When these results are combined, the final result is and the sample variance (square of the SD) of the 0/1 observations is The sample proportion is the mean of n of these observations, so the standard error of the proportion is calculated like the standard error of the mean, that is, the SD of one of them divided by the square root of the sample size or Copyright © 1998 Gerard E. Dallal
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with Friends What is the Standard Error? The standard error is an estimate of the standard deviation of a statistic. This lesson shows how to compute the standard error, based on http://www.jerrydallal.com/lhsp/psd.htm sample data. The standard error is important because it is used to compute other measures, like confidence intervals and margins of error. Notation The following notation is helpful, when we talk about the standard deviation and the standard error. Population parameter Sample statistic N: Number of observations in the population n: Number of observations in the sample Ni: Number of observations in population i http://stattrek.com/estimation/standard-error.aspx?Tutorial=AP ni: Number of observations in sample i P: Proportion of successes in population p: Proportion of successes in sample Pi: Proportion of successes in population i pi: Proportion of successes in sample i μ: Population mean x: Sample estimate of population mean μi: Mean of population i xi: Sample estimate of μi σ: Population standard deviation s: Sample estimate of σ σp: Standard deviation of p SEp: Standard error of p σx: Standard deviation of x SEx: Standard error of x Standard Deviation of Sample Estimates Statisticians use sample statistics to estimate population parameters. Naturally, the value of a statistic may vary from one sample to the next. The variability of a statistic is measured by its standard deviation. The table below shows formulas for computing the standard deviation of statistics from simple random samples. These formulas are valid when the population size is much larger (at least 20 times larger) than the sample size. Statistic Standard Deviation Sample mean, x σx = σ / sqrt( n ) Sample proportion, p σp = sqrt [ P(1 - P) / n ] Difference between means, x1 - x2 &si
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 http://stats.stackexchange.com/questions/159204/how-to-calculate-the-standard-error-of-a-proportion-using-weighted-data Us Learn more about Stack Overflow the company Business Learn more about hiring https://www.youtube.com/watch?v=7yG0OdKDaAQ developers 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 takes a minute: Sign up Here's how it works: Anybody can standard error ask a question Anybody can answer The best answers are voted up and rise to the top How to calculate the standard error of a proportion using weighted data? up vote 3 down vote favorite I know the "textbook" estimate of the standard error of a proportion is $SE=\sqrt{\frac{p(1-p)}{n}}$, but does this hold up when the data are weighted? standard-error proportion weighted-data share|improve this question edited Jun standard error of 29 '15 at 20:14 whuber♦ 145k17281540 asked Jun 29 '15 at 17:38 simudice 303 This is the root of the inverse of the Fisher information for a binomial distribution. The Fisher information is the variance of the expected value of the observed information. It is the standard deviation of the expected error. This expression should be valid for all binomial distributions. In practice, if the probability is quite close to one or to zero while you have few samples, the value given by the expression might have large error. Make sure your sample sizes are large enough. –EngrStudent Jun 29 '15 at 17:59 add a comment| 1 Answer 1 active oldest votes up vote 5 down vote accepted Yes, this formula generalizes in a natural way. Standardize the (positive) weights $\omega_i$ so they sum to unity. In a simple random sample $X_1, \ldots, X_n$ where each $X_i$ independently has a Bernoulli$(p)$ distribution and weight $\omega_i$, the weighted sample proportion is $$\bar X = \sum_{i=1}^n \omega_i X_i.$$ Since the $X_i$ are independent and each one has variance $\text{Var}(X_i) = p(1-p)$, the sampling variance of the proportion therefore is $$\text{Var}(\bar X) = \sum_{i=1}^n \text{Var}(\omega_i X_i) = p(1-p)\sum_{i=1}^n\omega_i^2.$$ T
lahat Learn more You're viewing YouTube in Filipino. Switch to another language: English | View all Isara Oo, panatilihin ito I-undo Isara Ang video na ito ay hindi magagamit. Queue ng PapanoorinQueueQueue ng PapanoorinQueue Alisin lahatIdiskonekta Naglo-load... Queue ng Papanoorin Queue __count__/__total__ Large Sample Standard Error 2 sample proportion James Gray Mag-subscribeNaka-subscribeMag-unsubscribe7373 Naglo-load... Naglo-load... Gumagawa... Idagdag sa Gusto mo bang panoorin itong muli sa ibang pagkakataon? Mag-sign in upang idagdag ang video na ito sa isang playlist. Mag-sign in Ibahagi Higit pa I-ulat Kailangan mo bang iulat ang video? Mag-sign in upang mag-ulat ng hindi angkop na nilalaman. Mag-sign in Transcript Mga Istatistika 2,835 (na) panonood 2 Gusto mo ba ang video na ito? Mag-sign in upang magbigay ng iyong opinyon. Mag-sign in 3 1 Hindi mo ba gusto ang video na ito? Mag-sign in upang magbigay ng iyong opinyon. Mag-sign in 2 Naglo-load... Naglo-load... Transcript Hindi ma-load ang interactive na transcript. Naglo-load... Naglo-load... Ang rating ay available kapag ang video ay na-rent. Hindi available ngayon ang feature na ito. Pakisubukang muli sa ibang pagkakataon. Na-publish noong Nob 24, 2012Find the standard error for 2 large sample proportions. Kategorya Edukasyon Lisensya Lisensya ng Pagpapatungkol ng Creative Commons (pinapayagan ang muling paggamit) Magpakita nang higit pa Magpakita nang mas kaunti Naglo-load... I-autoplay Kapag naka-enable ang autoplay, awtomatikong susunod na magpe-play ang isang iminumungkahing video. Susunod Stats: Sampling Distribution of a Proportion and Standard Error - Tagal: 16:52. BurkeyAcademy 5,450 (na) panonood 16:52 Sampling Distribution for Sample Proportion - Tagal: 18:42. craig sapp 9,609 (na) panonood 18:42 Statistics 101: Estimating Sample Size Requirements - Tagal: 37:42. Brandon Foltz 86,797 (na) panonood 37:42 Standard Error - Tagal: 7:05. Bozeman Science 171,662 (na) panonood 7:05 Standard Deviation for Proportions - Tagal: 4:30. Success@GC 2,639 (na) panonood 4:30 Sample Proportions - Tagal: 3:09. statslectures 33,517 (na) panonood 3:09 Standard error of the mean - Tagal: 4:31. DrKKHewitt 15,693 (na) panonood 4:31 Statistics 101: Standard Error of the Mean - Tagal: 32:03. Brandon Foltz 68,062 (na) panonood 32:03 Confidence Intervals for Sample Proportions - Tagal: 9:36. Daniel Schaben 34,002 (na) panonood 9:36 How to calculate standard error for the sample mea