![]() ![]() ![]() ![]() If you’ve got a large standard error, your statistic is likely to be less accurate. The standard error tells you how accurate the mean of a given sample is relative to the true population mean. It is important in a test or experiment that you use a random sample method to get the most accurate data point model, so that your barplot or other data model example is the most accurate, and closest to a normal distribution. This statistic is commonly included in summary statistics and descriptive statistics views. This is generated by repeatedly sampling the mean (or other statistic) of the population (and sample standard deviation) and examining the variation within your samples. The standard error of a statistic is the estimated standard deviation of the sampling distribution. 1.519607 Uses of the Standard Error in R > sd(product_tests, na.rm=TRUE)/sqrt(length(na.omit(product_tests))) ![]()
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