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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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