MKT-300 Lecture Notes - Lecture 8: Simple Random Sample, Sampling Error, Pyramid Scheme
Document Summary
No(cid:374)-probability sample we do(cid:374)"t (cid:272)are if it accurately represents the population: convenience sample. Pick people based on judgements: quota sample. Force sample to fit: snowball sample. Chain- send this to five people a(cid:374)d the(cid:374) get the(cid:373) to et(cid:272). Relations there wo(cid:374)"t (cid:271)e a wide distri(cid:271)utio(cid:374) Probability sample we do(cid:374)"t wa(cid:374)t to i(cid:373)pose li(cid:373)its: equal chance of being selected remove any errors in bias, everyone has the same opportunity to be picked, completely random, purest representation of a sample. So slightly chosen but within that group its completely unbiased. Forcing people into clusters to see if they share characteristics. Imply a rule to try to be as random as possible. Go through the phone book and choose every tenth person. The difference between the scores for these individual questions and overall loyalty score is an error. Sampling error: occurs when a sample somehow does represent the target population.
