STAT 1034 Lecture Notes - Lecture 5: Sampling Distribution, Randomized Experiment, Random Variable
Document Summary
The value of a statistic is known when we have taken the sample, but it can change from sample to sample. We often use a statistic to estimate an unknown parameter: ex: roll a die 24 times and want the percent or proportion of the tosses resulting in a 1 face up. Say in the 24 tosses 1 appears 6 times. The percent or proportion of times 1 appears is: assuming the die is fair the corresponding parameter value, = (cid:2874)(cid:2870)(cid:2872)=(cid:2869)(cid:2872)=. (cid:884)(cid:887), p = 1/6 1/4 = would be: p = 1/6. In inference we would ask: is the die a fair die based on our result of the 24 tosses? : sampling variability: if we toss the die another 24 times we may get 6 ones. The value of would vary from sample to sample (bc life isn"t perfect) these values will form the sampling distribution.
