Ad
related to: calculation of sample size formula
Search results
Results from the WOW.Com Content Network
For example, person 1 takes 25 minutes, person 2 takes 30 minutes, ..., person 100 takes 20 minutes. Add up all the commute times and divide by the number of people in the sample (100 in this case). The result would be your estimate of the mean commute time for the entire population.
For example, in the R statistical computing environment, this value can be obtained as fisher.test(rbind(c(1,9),c(11,3)), alternative="less")$p.value, or in Python, using scipy.stats.fisher_exact(table=[[1,9],[11,3]], alternative="less") (where one receives both the prior odds ratio and the p -value).
This approximate formula is for moderate to large sample sizes; the reference gives the exact formulas for any sample size, and can be applied to heavily autocorrelated time series like Wall Street stock quotes.
Cohen's h has several related uses: It can be used to describe the difference between two proportions as "small", "medium", or "large". It can be used to determine if the difference between two proportions is "meaningful". It can be used in calculating the sample size for a future study.
The formula for the population standard deviation (of a finite population) can be applied to the sample, using the size of the sample as the size of the population (though the actual population size from which the sample is drawn may be much larger).
Sampling (statistics) In statistics, quality assurance, and survey methodology, sampling is the selection of a subset or a statistical sample (termed sample for short) of individuals from within a statistical population to estimate characteristics of the whole population. The subset is meant to reflect the whole population and statisticians ...
Typical rules of thumb: the sample size should be 50 observations or more. For large sample sizes, the t -test procedure gives almost identical p -values as the Z -test procedure. Other location tests that can be performed as Z -tests are the two-sample location test and the paired difference test.
Margin of error. Probability densities of polls of different sizes, each color-coded to its 95% confidence interval (below), margin of error (left), and sample size (right). Each interval reflects the range within which one may have 95% confidence that the true percentage may be found, given a reported percentage of 50%.
The figure shows the ratio of the estimated standard deviation to its known value (which can be calculated analytically for this digital filter), for several settings of α as a function of sample size n.
The sample extrema can be used for a simple normality test, specifically of kurtosis: one computes the t-statistic of the sample maximum and minimum (subtracts sample mean and divides by the sample standard deviation ), and if they are unusually large for the sample size (as per the three sigma rule and table therein, or more precisely a ...