Prob/Stats: Chapter 1 Vocabulary

by Amber Hunnicutt

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 convenience sampling data that results when the number of possible values is either a finite number or a "countable number" observational study the collection of data from every member of the population sample observations (such as measurements, genders, survey responses) that have been collected experiment we first divide the population area into sections, then randomly select some of those clusters, and then choose all the members from those selected clusters placebo effect study in which data are collected from the past by going back in time cross-sectional a numerical measurement describing some characteristic of a population systematic sampling consist of numbers representing counts or measurements population we subdivide the population into at least two different subgroups that share the same characteristics, then we draw a sample from each subgroup parameter the difference between a sample result and the true population result prospective observes and measures specific characteristics, but doesn't attempt to modify the subjects being studied sampling error study in which data are observed, measured, and collected at one point in time random sample occurs when an untreated subject incorrectly believes that he or she is receiving a real treatment and reports an improvement in symptoms qualitative data the complete collection of all elements to be studied blinding study in which data are collected in the future from groups sharing common factors nonsampling error data that results from infinitely many possible values that correspond to some continuous scale that covers a range of values without gaps, interruptions, or jumps statistic procedure used in experiments whereby the subject doesn't know whether he or she is a receiving a treatment or a placebo stratified sampling a numerical measurement describing some characteristic of a sample data a subcollection of members selected from a population cluster sampling can be separated into different categories that are distinguished by some nonnumerical characteristic retrospective occurs in an experiment when the experimenter is not able to distinguish between the effects of different factors discrete we simply use results that are very easy to get census we select some starting point and then select every nth element in the population quantitative data members from the population are selected in such a way that each individual member has an equal chance of being selected continuous applies some treatment and then proceeds to observe its effects on the subjects confounding occurs when the sample data are incorrectly collected, recorded, or analyzed

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