You can see that when the samples are small the sample mean isn’t necessarily a good representation of the population that it was sampled from–and that is not a good thing.įor further reading see the Law of Large Numbers.Though the y-values vary here, remember that if the sample were a good estimate of the population, the y-values should be very close to 0. The y-axis shows what the mean is for a sample of that particular size.Each point on the zig-zag line is the mean calculated from a random sample.The animation above shows the values of means calculated from increasingly larger samples: small samples on the left and larger samples to the right (on the x-axis).Pressing ‘Play’ on the plot below will illustrate this concept. On the other hand, the larger the sample, the closer the sample size appraches the population size, and the more reliable the sample estimate becomes. How reliably does the mean of a sample represent the population mean? Warning: if a small sample has been used, the sample mean may not be a reliable at all! Estimates from small samples are subject to the whims of randomness. Remember that the sample mean is an estimate of the entire population’s mean (which would often be impossibly large to measure). To make this more efficient, instead of writing “ \( It’s not typically used in statistics, and we won’t cover it further here.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |