Ap Statistics Standard Error
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Ap Stats Standard Deviation
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Standard Error Formula
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Standard Error Definition
CodeComputer animationArts & humanitiesArt historyGrammarMusicUS historyWorld historyEconomics & financeMicroeconomicsMacroeconomicsFinance & capital marketsEntrepreneurshipTest standard error interpretation prepSATMCATGMATIIT JEENCLEX-RNAP* Art HistoryCollege AdmissionsDonateSign in / Sign upSearch for subjects, skills, and videos Main content To log standard error of proportion in and use all the features of Khan Academy, please enable JavaScript in your browser. Sampling distributionsSample meansCentral limit theoremSampling distribution of the sample meanSampling distribution of the sample mean http://stattrek.com/statistics/dictionary.aspx?definition=standard%20error 2Standard error of the meanSampling distribution example problemConfidence interval 1Difference of sample means distributionCurrent time:0:00Total duration:15:150 energy pointsStatistics and probability|Sampling distributions|Sample meansStandard error of the meanAboutTranscriptStandard Error of the Mean (a.k.a. the standard deviation of the sampling distribution of the sample mean!). Created by Sal Khan.ShareTweetEmailSample meansCentral limit theoremSampling distribution of the sample meanSampling distribution of the sample mean 2Standard https://www.khanacademy.org/math/statistics-probability/sampling-distributions-library/sample-means/v/standard-error-of-the-mean error of the meanSampling distribution example problemConfidence interval 1Difference of sample means distributionTagsSampling distributionsVideo transcriptWe've seen in the last several videos you start off with any crazy distribution. It doesn't have to be crazy, it could be a nice normal distribution. But to really make the point that you don't have to have a normal distribution I like to use crazy ones. So let's say you have some kind of crazy distribution that looks something like that. It could look like anything. So we've seen multiple times you take samples from this crazy distribution. So let's say you were to take samples of n is equal to 10. So we take 10 instances of this random variable, average them out, and then plot our average. We plot our average. We get 1 instance there. We keep doing that. We do that again. We take 10 samples from this random variable, average them, plot them again. You plot again and eventually you do this a gazillion times-- in theory an infinite number of times-- and you're going to approach t
repeatedly randomly drawn from a population, and the proportion of successes in each sample is recorded (\(\widehat{p}\)),the https://onlinecourses.science.psu.edu/stat200/node/43 distribution of the sample proportions (i.e., the sampling distirbution) can be approximated by a normal distribution given that both \(n \times p \geq 10\) and \(n \times (1-p) \geq 10\). This is known as theRule of Sample Proportions. Note that some textbooks use a minimum of 15 instead of 10.The mean standard error of the distribution of sample proportions is equal to the population proportion (\(p\)). The standard deviation of the distribution of sample proportions is symbolized by \(SE(\widehat{p})\) and equals \( \sqrt{\frac {p(1-p)}{n}}\); this is known as thestandard error of \(\widehat{p}\). The symbol \(\sigma _{\widehat p}\) is also used to signify the standard deviation ap stats standard of the distirbution of sample proportions. Standard Error of the Sample Proportion\[ SE(\widehat{p})= \sqrt{\frac {p(1-p)}{n}}\]If \(p\) is unknown, estimate \(p\) using \(\widehat{p}\)The box below summarizes the rule of sample proportions: Characteristics of the Distribution of Sample ProportionsGiven both \(n \times p \geq 10\) and \(n \times (1-p) \geq 10\), the distribution of sample proportions will be approximately normally distributed with a mean of \(\mu_{\widehat{p}}\) and standard deviation of \(SE(\widehat{p})\)Mean \(\mu_{\widehat{p}}=p\)Standard Deviation ("Standard Error")\(SE(\widehat{p})= \sqrt{\frac {p(1-p)}{n}}\) 6.2.1 - Marijuana Example 6.2.2 - Video: Pennsylvania Residency Example 6.2.3 - Military Example ‹ 6.1.2 - Video: Two-Tailed Example, StatKey up 6.2.1 - Marijuana Example › Printer-friendly version Navigation Start Here! Welcome to STAT 200! Search Course Materials Faculty login (PSU Access Account) Lessons Lesson 0: Statistics: The “Big Picture” Lesson 1: Gathering Data Lesson 2: Turning Data Into Information Lesson 3: Probability - 1 Variable Lesson 4: Probability - 2 Variables Lesson 5: Probability Distributio
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