Stats Final Exam

# Stats Final Exam - Statistics the study of how to collect...

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Statistics - the study of how to collect, organize, analyze and interpret info, Population - the collection of individuals or items of interest, Census - measurements from an entire pop are used, Sample - the subset of the pop on which we take measurements, Data - the measurements we collect, Individuals - the objects described by a set of data, Variable - any characteristic of and individual that can take different values for different individuals, Descriptive stats - methods of summarizing a set of data (no errors because you are summarizing the data you have) ex: sports stats, avg. GPA for students, car sales for the yr., # of students who live in Lex., Inferential stats - methods of making inference about a pop based on the info in the sample; collect data from a subset or sample of pop and use to estimate pop (is error because you don’t have all data, you have a subset of data) ex: presidential approval rating, Observational study - observes individuals and measures variables of interest but doesn’t attempt to influence responses ex: outcome of election predicted by polls, Sample survey- when data is collected by asking questions and recording answers; most common type of observational study ex: opinion polls, consumer surveys, teacher evals, Experiment - deliberately imposes some treatment on individuals to observe responses, Simulation - numerical facsimile of real world phenom; not used unless necessary, expensive) ex: crash tests, Bias - prejudice in one direction, Convenience sampling - uses results or data that are conveniently & readily obtained, can be extremely biased and shouldn’t be generalized to the overall pop or for inferential data, Voluntary response sample - common type of convenience sample that is selected by subjects volunteering, typically over represents people with strong opinions ex: comment cards, Random sample - sample determined completely by chance, is a representative sample, Simple random sample - sample of n measurements from a population selected in such a manner that every sample of size n from the population has equal probability of being selected, most common and all course is based on Stratified sampling - population is divided into at least two distinct strata or groups, a simple random sample is drawn from each, Systematic sampling - select a random starting point, select every fourth person in the sample, Cluster sampling -divide pop onto sections, randomly select the sections or clusters, Variability - describes the spread of values; we want the possible values of a statistic to not include bias and have a small amount of v.; to eliminate bias use random sampling; to control v. use a larger sample, Statistic - a numerical characteristic of sample, Parameter - a numerical characteristic of a population, Margin of error - can be calculated from the sampling variability; We can say with 95% confidence that the amount by which a proportion obtained from a sample will differ from the population proportion will not exceed Suppose you take a sample of 1600 adults and 800 enjoy amusement park rides. the sample proportion that

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## This note was uploaded on 07/12/2011 for the course STATS 200 taught by Professor Bradley,w during the Fall '10 term at KCTCS.

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Stats Final Exam - Statistics the study of how to collect...

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