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characteristics or attributes that can assume different values. A generalization unknown quantity "X" |
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measurements of observations collected now or in the past |
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a variable selected in a random fashion "values determined by chance..." |
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assumes a singular value, counted, {Fixed #} -things we can count |
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A value that falls within some range, measured x: temp, length, time |
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descriptions- not calculated ex: Name, address, phone #, SSN |
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has a dimension and is used for calculations ex: height, weight, length, $$ |
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means 'to give a name to' ex: zipcode, sex, political party, major study |
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things we classify in some order ex: (A-F), rankings, (1st, 2nd,....), first letter of last name |
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ranked and ordered info ex: difference in SAT scores, I.Q, Temps |
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measurements expressed as ratios ex: height 2x taller, time 4x faster |
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Large, large numbers ex: set of all men 20-25, all cars made in 1993 -hard to work with |
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A Large sample greater than or equal to 30 a small sample is less than 30-easier to work with |
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The organized and summarized data calculated/ presented as 1. Tables of Data 2. Graphs 3.Charts |
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Use samples to make estimations or a supposition abut a population |
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Everyone has an equal chance of being selected. If you replace its not completely random, only if u put back whatever you draw. |
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Selecting members from each segment of a population. Strata- population divided into subsets i.e. income, age, race, gender, etc. |
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When a population falls into a natural subset of the population (geographic) |
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A developed (schemed) way of selecting from a population i.e. 1st, 3rd, 5th, ect., of population even, odd, every 10th, etc. |
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Sampling the available people or items for a study--this can lead to a biased study |
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Patient does not know whether they are getting medicine or placebo |
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neither patient nor doctor knows who is getting what |
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Data collected from entire population. population of employees, US census 2010 |
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when studies are too large, impractical or dangerous--crash tests |
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testing a select group of people |
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