AP Statistics Review Week 3 Gathering Data

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AP Statistics Review Week 3 Gathering Data Advanced Placement AAP Review will be held in room 315 and 312 on Tuesdays and Thursdays. The week of April 6 th we will be reviewing Gathering Data The session will begin in room 315 with a brief review of the weekly topic. Instruction will be from 3:15 pm to 3:30 pm Once we have reviewed the topic you may begin practicing the questions in your review packet. Answers will be posted in room 315 and 312 all week and will be posted on line after 3:00 pm on Friday the week of review. If you have difficulty with a question look at the detailed answer postings BEFORE you ask your teacher for help. Get a hint.don T COPY THE ANSWER!!! THAT IS NOT HELPFUL!! When you have completed a question REFLECT!!!! Ask yourself what skill you used to solve that problem and write that down!! Once we have completed the weekly review, keep it to study from as we get closer to the exam.

Gathering Data Brief Review This unit is all about the APPROPRIATE way to collect data. If you don t collect data in an appropriate way it is not at all useful. This unit is full of vocabulary one of the objectives of the College Board is to make sure you know and can use the vocabulary of statistics!! Know the difference between an Experiment and an Observational Study the vocabulary word they are looking for is RANDOM placement into TREATMENT groups. When you talk about BIAS don t worry about using words like undercoverage and Non-Response as much as you talk about the groups in the population that will be over-represented and under-represented in your sample as a result of the bias. Recall there is a difference between bias that comes from the sampling TECHNIQUE and bias that results from the QUESTION. Questioning bias is known as RESPONSE bias. Make sure you can run a simulation and design an experiment. Make sure you know how to create a plan for random selection, ignore repeats if you need to??? This is where we used THE HAT! But make sure you can do it with or without THE HAT! A well designed experiment with random placement into treatment groups can show CAUSE and EFFECT. Here is a list of vocabulary I found on the internet. biased any systematic failure of a sampling method to represent its population block a subdivision of the population

census a sample that consists of the entire population cluster sampling design in which entire groups are chosen at random completely randomized type of experiment in which all experimental units have an equal chance of receiving any treatment confounding when the levels of one factor are associated with the levels of another factor so their effects cannot be separated control aspects of the experiment that we know may have an effect on the response, but that are not the factors being studied control group experimental units assigned to a baseline treatment level convenience sampling design where individuals are chosen based on who is easily available double blind neither the subjects nor the people who have contact with them know which treatment a subject has received experimental units individuals on which an experiment is done experiments study in which subjects are randomly assigned to treatments

factor variable whose levels are controlled by the experimenter heterogeneous not similar in makeup homogeneous similar in makeup level specific values that the experimenter chooses a factor matched pairs type of study in which subjects who are similar in ways not under study may be grouped together and then compared with each other on the variables of interest multistage sampling schemes that combine several sampling methods nonresponse type of bias that is problematic because the intended sample is incomplete observational study study based on data in which no treatments have been assigned to subjects outcome an individual result of a component of a simulation placebo treatment known to have no effect, administered so that all groups experience the same conditions

placebo effect the tendency of many human subjects to show a response even when administered a fake treatment population the entire group of individuals or instances about whom we hope to learn prospective observational study in which subjects are followed to observe future outcomes random behavior an occurrence for which we know what outcomes could happen, but not which particular values will happen randomization process by which each individual is given a fair chance of selection response type of bias that is problematic because false information may be given retrospective observational study in which subjects are selected and then their previous conditions or behaviors are determined sample a (representative) subset of a population, examined in hope of learning about a population sample survey a study that asks questions of a sample drawn from some population in the hope of learning something about the entire population sampling frame a list of individuals from whom the sample is drawn

sampling variability the natural tendency of randomly drawn samples to differ, one from another simple random sampling design in which each set of n elements in the population has an equal chance of selection simulation models random events by using random numbers to specify outcomes with relative frequencies that correspond to the true real-world relative frequencies we are trying to model single blind when either the subjects or the people who have contact with them do not know which treatment a subject has received statistically significant when an observed difference is too large to believe that it is likely to have occurred naturally strata when groups of experimental units are similar, they are gathered into these groups stratified sampling design in which the population is divided into several strata, and random samples are then drawn from each stratum subjects people who are studied systematic sample drawn by select an individual from a list and then each of the next N individuals from the sampling frame treatment the process or intervention applied to randomly assigned experimental units

trial the sequence of several components representing events that we are pretending will take place undercoverage type of bias that is problematic because some groups are not represented in the sample voluntary response sampling design where individuals can choose on their own whether to participate in the sample voluntary response type of bias that is problematic because those who volunteer tend to have strong negative opinions wording bias a type of response bias where the question is posed to achieve a desired result

1997:

Workshop Materials:

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FREE RESPONSE 2013 #2

Free Response 2011 #3

Free Response 2011 Form B #2

Free Response 2010 #1