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| how to collect, sumarize, analyze data w/ graphs/numerical methods |
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| derived from descriptive stats & probability- make generalization, conclusions, decisions |
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| characteristic/subset of population |
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| summary measure that is computer to describe char. of population |
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| always round up- not normal rules |
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| (qualitative) if categories can't be ordered (m f) |
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| (qualitative) if categories can be ordered (letter grade) |
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| (quantitative) assumes finite or countable possible values |
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| (quantitative) infinite, noncountable possible values (time) |
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| category/group into which data classified |
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| graph of cumulative distribution |
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| (data symmetrical) 68% fall w/in 1 SD, 95% fall w/in 2SD, 99.7% fall w/in 3SD |
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| empirical rule for z scores |
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| 68% have z scores between -1&1, 95% bt -2&2, 99.7% bt -3&3 |
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| z scores: mild outlier | extreme outlier |
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| z score bt 2 &3 | z score above 3. more sensitive than quartile method |
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| quartiles: mild outlier | extreme outlier |
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| bt UIF/UOF or LIF/LOF | past UOF or LOF |
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| descending- only for categorical data |
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| any process that can be repeated, has 1 single outcome, result cannot be predicted w/ certainty |
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| any single outcome of a stat. exp. for ex Heads or Tails |
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| unusual event | usual event |
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| has prob <0.05 | has prob ≥ 0.05 |
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| if P(A|B)=P(A) or P(AandB)=P(A)xP(B) |
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| events are mutually exclusive |
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| discrete random variable | continuous random variable |
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| countable (finite or infinite) | uncountable (interval) |
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| 90%-1.645; 95%-1.96; 99.7%-2.575 |
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| has single trial & only 2 mutually exclusive outcomes (M&F), P(Success) is same in each trial, all trials are independent |
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| p>0.5- left skewed; p=0.5- sym; p<0.5- right skewed |
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