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Producing Data Population – Entire group of individuals or objects that we want information about. Defined in terms of what we want to know. Sample – The part of the population that we actually use to gather information and draw conclusions about the whole population.

Sampling Designs –S–SRS – simple random sample –E–Every individual unit or set of units has an equal chance of being selected Stratified Random Sample – First divides population into similar groups called strata. Then does a simple random sample in each stratum. Then combines to form a full sample.

Multistage Sampling – When you take an SRS of a large category, then take another SRS from a smaller category within those chosen from the larger category and so on and so on. Example: – Pick counties by SRS –T–Then pick city by SRS –T–Then pick townships by SRS... Then pick block by SRS

Experiment Designs Block Design – A group of experimental units or subjects that are similar in ways that are expected to affect the response to the treatment. Make similar groups then do an SRS in each group and combine –Similar to stratified design in sampling –A form of control

Matched Pairs 1 – Each subject receives both treatments in random order. –Example: Pepsi vs. Coke taste test – randomly pick which you taste first Matched Pairs 2 – Each subject or unit serves as its own control. Before and After tests –Example: Take subjects heart rate, then subject does 25 jumping jacks and takes heart rate again. Take difference in measurements. Compare difference to zero (no change)

Remember that every sample is only an estimate of an entire population and the results obey the laws of probability that govern chance behavior. Larger samples give more accurate results because they have less variability. Look at #41 page 282 Homework p. 261 #15 p. 263 #22 p.282 &283 #’s 40, 43 & 44 For # 40 use calc and seed at 100