STA 309 Chapter Notes - Chapter 8-1: Statistical Parameter, Sampling Bias, Statistic
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Idea 1: sample - examine a part of the whole. Examining an entire population is impractical, too expensive, and not feasible, so a smaller group of individuals is used - a sample. A biased sample size, produces misleading information that is flawed: to make the sample as representative as possible, the best strategy is to select individuals for the sample at random. Idea 3: the sample size is what matters. Models of data (cid:272)a(cid:374) gi(cid:448)e us su(cid:373)(cid:373)aries that (cid:449)e (cid:272)a(cid:374) lear(cid:374) fro(cid:373) a(cid:374)d use e(cid:448)e(cid:374) though they do(cid:374)"t fit ea(cid:272)h data value exactly. We call the key numbers in those models parameters. Sometimes a parameter used in a model for a population is called a population parameter. We usually obtain a statistic from a sample and use it to estimate a population parameter: are usually unknowable; sample statistics is used to estimate them. Any summary found from the data is a statistic.
