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AP Statistics Chapter 4 Flashcards

Sampling and Surveys

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6738273724BiasThe design of a statistical study shows bias if it systematically favors certain outcomes.0
6738273725CensusA study that attempts to collect data from every individual in the population.1
6738273726Cluster sampleTo take a cluster sample, first divide the population into smaller groups. Ideally, these clusters should mirror the characteristics of the population. Then choose an SRS of the clusters. All individuals in the chosen clusters are included in the sample.2
6738273727Convenience sampleA sample selected by taking the members of the population that are easiest to reach; particularly prone to large bias.3
6738273728Double-blindAn experiment in which neither the subjects nor those who interact with them and measure the response variable know which treatment a subject received.4
6738273729Margin of errorA numerical estimate of how far the sample result is likely to be from the truth about the population due to sampling variability.5
6738273730NonresponseOccurs when a selected individual cannot be contacted or refuses to cooperate; an example of a nonsampling error.6
6738273731Nonsampling errorThe most serious errors in most careful surveys are nonsampling errors. These have nothing to do with choosing a sample—they are present even in a census. Some common examples of nonsampling errors are nonresponse (people don't answer), response bias (people lie), and errors due to question wording.7
6738273732PopulationIn a statistical study, the entire group of individuals about which we want information.8
6738273733Random samplingThe use of chance to select a sample; is the central principle of statistical sampling; allows us to infer results to the population9
6738273734Response biasA systemic pattern of incorrect responses; "people lie"10
6738273735SampleThe part of the population from which we actually collect information. We use information from this to draw conclusions about the entire population.11
6738273736Sampling errorMistakes made in the process of taking a sample that could lead to inaccurate information about the population. EX. bad sampling methods (convenience and voluntary response) and undercoverage12
6738273739Simple random sample (SRS)Gives every possible sample of a given size the same chance to be chosen. We often choose this type of sample by labeling the members of the population and using random digits to select the sample.13
6738273740StrataGroups of individuals in a population that are similar in some way that might affect their responses.14
6738273741Stratified random sampleFirst classify the population into groups of similar individuals (mini populations). Then choose a separate SRS from each stratum to form the full sample.15
6738273742Table of random digitsA long string of the digits 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 with these properties: • Each entry in the table is equally likely to be any of the 10 digits 0 through 9. • The entries are independent of each other. That is, knowledge of one part of the table gives no information about any other part.16
6738273743UndercoverageOccurs when some members of the population are left out of the sampling frame; a type of sampling error.17
6738273744Voluntary response samplesPeople decide whether to join a sample based on an open invitation; particularly prone to large bias.18
6738273745Wording of questionsThe most important influence on the answers given to a survey. Confusing or leading questions can introduce strong bias, and changes in wording can greatly change a survey's outcome. Even the order in which questions are asked matters.19
6738273746BlockA group of experimental units that are known before the experiment to be similar in some way that is expected to affect the response to the treatments.20
6738273747Completely randomized designWhen the treatments are assigned to all the experimental units completely by chance.21
6738273748ConfoundingWhen two variables are associated in such a way that their effects on a response variable cannot be distinguished from each other.22
6738273750Control groupAn experimental group whose primary purpose is to provide a baseline for comparing the effects of the other treatments. Depending on the purpose of the experiment, this group may be given a placebo or an active treatment23
6738273751Double-blindAn experiment in which neither the subjects nor those who interact with them and measure the response variable know which treatment a subject received.24
6738273752ExperimentDeliberately imposes some treatment on individuals to measure their responses.25
6738273754Explanatory variableA variable that helps explain or influences changes in a response variable.26
6738273755FactorThe explanatory variables in an experiment are often known as these27
6738273757Lurking variableA variable that is not among the explanatory or response variables in a study but that may influence the response variable.28
6738273758Matched pairA common form of blocking for comparing just two treatments. Often each subject receives both treatments in a random order. In others, each subject is matched to another subject who is very similar and results are compared.29
6738273759Observational studyObserves individuals and measures variables of interest but does not attempt to influence the responses.30
6738273760PlaceboAn inactive (fake) treatment.31
6738273761Placebo effectDescribes the fact that some subjects respond favorably to any treatment, even an inactive one (placebo).32
6738273762Random assignmentUse some chance process to assign experimental units to treatments. This helps create roughly equivalent groups of experimental units by balancing the effects of lurking variables that aren't controlled on the treatment groups. Allows us to infer cause and effect.33
6738273763Randomized block designStart by forming blocks consisting of individuals that are similar in some way that is important to the response. Random assignment of treatments is then carried out separately within each block.34
6738273765Response variableA variable that measures an outcome of a study.35
6738273768SubjectsExperimental units that are human beings.36
6738273769TreatmentA specific condition applied to the individuals in an experiment. If an experiment has several explanatory variables, a treatment is a combination of specific values of these variables.37
6738273771Inference about cause and effectRequires a well-designed experiment in which the treatments are randomly assigned to the experimental units.38
6738273772Inference about the populationUsing information from a sample to draw conclusions about the larger population. Requires that the individuals taking part in a study be randomly selected from the population of interest.39

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