2/17/2023 0 Comments Groundhog day accuracy stats![]() ![]() ![]() How can we quantify the accuracy of this estimate, given its sample size? ![]() The mean of our sample of 50 giraffes from Island 1 was: mean(heights_island1) # 9.714141 We’ll revisit this question a few times below. We can make some inferences about whether or not this is a good guess based on what we learn from our sample of giraffe heights. For example, say that we guess that the population mean value of giraffe heights on Island 1 is less than 11 cm. Subsets of data are of course limited, so it’s therefore important to acknowledge that the strength of the conclusions drawn about the population is dependent on the precision of the sample estimate. Statistical inference uses math to draw conclusions about the population based on a subset of the full picture (i.e. a sample). One reason we care about our sample estimate’s accuracy is because we want to be able to answer questions about the population by making inferences. There are stricter, more formal statistical uses for these words, but for right now, we’re going to ignore these nuances so that we can move on with understanding these concepts in broad strokes. We’re using the laymen’s application of these terms to refer to the long-run variability of estimates produced from repeated, independent trials. ![]() A note about language: here, words like “accuracy”, “precision”, and “uncertainty” are used in a rather fast and loose way. ![]()
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