Effect Of Increasing Sample Size On Standard Error
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What Happens To Standard Error When Sample Size Increases
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If The Size Of The Sample Is Increased The Standard Error Will
Affects Standard Error Related Book Statistics For Dummies, 2nd Edition By Deborah J. Rumsey The size (n) of a statistical sample affects the standard error for that sample. Because n is in the denominator of the standard error formula, the standard error decreases as n increases. It makes sense that having more
Effect Of Increasing Sample Size On Probability
data gives less variation (and more precision) in your results.
Distributions of times for 1 worker, 10 workers, and 50 workers. Suppose X is the time it takes for a clerical worker to type and send one letter of recommendation, and say X has a normal distribution with mean 10.5 minutes and standard deviation 3 minutes. The bottom curve in the preceding figure shows the distribution of X, the individual times for all clerical workers in the population. According to the Empirical Rule, almost all of the values are within 3 standard deviations of the mean (10.5) -- between 1.5 and 19.5. Now take a random sample of 10 clerical workers, measure their times, and find the average, each time. Repeat this process over and over, and graph all the possible results for all possible samples. The middle curve in the figure shows the picture of the sampling distribution of Notice that it's still cTour 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 Us Learn more about Stack Overflow the company Business Learn effect of increasing sample size on confidence interval more about hiring developers or posting ads with us Cross Validated Questions Tags Users Badges
Effect Of Increasing Sample Size On Power
Unanswered Ask Question _ Cross Validated is a question and answer site for people interested in statistics, machine learning, data analysis, data mining, and which of the following accurately describes the effect of increasing the sample size data visualization. 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 up and rise to the top Why does the standard http://www.dummies.com/education/math/statistics/how-sample-size-affects-standard-error/ deviation not decrease when I do more measurements? [duplicate] up vote 11 down vote favorite 6 This question already has an answer here: Difference between standard error and standard deviation 4 answers I made 100 measurements of a certain quantity, calculated mean and standard deviation (with MySQL), and got mean=0.58, SD=0.34. The std seemed too high relative to the mean, so I made 1000 measurements. This time I got mean=0.572, SD=0.33. I got frustrated by the high http://stats.stackexchange.com/questions/89456/why-does-the-standard-deviation-not-decrease-when-i-do-more-measurements standard deviation, so I made 10,000 measurements. I got mean=0.5711, SD=0.34. I thought maybe this was a bug in MySQL, so I tried to use the Excel functions, but got the same results. Why does the standard deviation remain high even though I do so many measurements? standard-deviation experiment-design share|improve this question edited Mar 11 '14 at 5:14 Jeromy Anglim 27.6k1393195 asked Mar 10 '14 at 14:03 Erel Segal-Halevi 4041313 marked as duplicate by Nick Cox, Glen_b♦, whuber♦ Mar 11 '14 at 12:00 This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question. add a comment| 3 Answers 3 active oldest votes up vote 7 down vote accepted The standard deviation is a measurement of the "spread" of your data. The analogy I like to use is target shooting. If you're an accurate shooter, your shots cluster very tightly around the bullseye (small standard deviation). If you're not accurate, they are more spread out (large standard deviation). Some data is fundamentally "all over the place", and some is fundamentally tightly clustered about the mean. If you take more measurements, you are getting a more accurate picture of the spread. You shouldn't expect to get less spread--just less error in your measurement of a fundamental characteristic of the data. If you have an inaccurate shooter
using Windows 95, 98 or NT. When asked if you want to install the sampling control, click on Yes. When we draw a sample from a population, and calculate a sample statistic such as the mean, we http://academic.udayton.edu/gregelvers/psy216/activex/sampling.htm could ask how well does the sample statistic (called a point estimate) represent the same value for the population? That is, if we calculate the mean of a sample, how close will it be to the mean of the population? Of course, the answer will change depending on the particular sample that we draw. But could we develop a measure that would at least give us an indication of how sample size well we expect the sample mean to represent the population mean? We could subtract the sample mean from the population mean to get an idea of how close the sample mean is to the population mean. (Technically, we don't know the value of the population mean -- if we knew the population mean, then there would be no sense in calculating the sample mean. But in theory, it is possible increasing sample size to get an arbitrarily good estimate of the population mean and we can use that estimate as the population mean.) That is, we can calculate how much the sample mean deviates from the population mean. But is this particular sample representative of all of the samples that we could select? It may or may not be. So, we should draw another sample and determine how much it deviates from the population mean. In fact, we might want to do this many, many times. We could then calculate the mean of the deviates, to get an average measure of how much the sample means differ from the population mean. The standard error of the mean does basically that. To determine the standard error of the mean, many samples are selected from the population. For each sample, the mean of that sample is calculated. The standard deviation of those means is then calculated. (Remember that the standard deviation is a measure of how much the data deviate from the mean on average.) The standard deviation of the sample means is defined as the standard error of the mean. It is a measure of how well the point estimate (e.g. the sample mean) represents the population parameter (e.g. the population mean.) If