KINE 2049 Lecture Notes - Confounding, Multistage Sampling, Cluster Sampling
17 Apr 2013
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>sample size is also important for statistical analysis. >try to select enough to account for attrition of subjects. attrition means people have exercised their right to quit at any time that they want. Every subject has an equal chance of being selected and the selection of one does not bias the chance of others. imagine lotto 649 the moment they pick #6 you can"t pick 7, 8, and 9 etc. if you pick every 10th person it influences the chance of the others being selected. Simple random selection - (pull from hat, or the table of random numbers) . you want to make sure that when you put names in a hat they are all the same size. this would be best if you used your student #"s as they are all the same size. with replacement - means name goes back into the hat. without replacement - means you name stays out of the hat.
